// Licensed to the .NET Foundation under one or more agreements.
// The .NET Foundation licenses this file to you under the MIT license.
namespace Aspire.Hosting.Foundry;
/// <summary>
/// Generated strongly typed model descriptors for Microsoft Foundry.
/// </summary>
public partial class FoundryModel
{
/// <summary>
/// Models published by Anthropic.
/// </summary>
public static partial class Anthropic
{
/// <summary>
/// Claude Fable 5 is our most intelligent Fable model and the best generally available model for coding and agents, with deeper reasoning for enterprise workflows.
/// </summary>
[AspireValue("FoundryModels")]
public static readonly FoundryModel ClaudeFable5 = new() { Name = "claude-fable-5", Version = "1", Format = "Anthropic" };
/// <summary>
/// Claude Haiku 4.5 delivers near-frontier performance for a wide range of use cases, and stands out as one of the best coding and agent models – with the right speed and cost to power free products and scaled sub-agents.
/// </summary>
[AspireValue("FoundryModels")]
public static readonly FoundryModel ClaudeHaiku45 = new() { Name = "claude-haiku-4-5", Version = "2", Format = "Anthropic" };
/// <summary>
/// Claude Mythos 5 (gated) is a new class of intelligence for cybersecurity, coding, and long-running agents. Only available as a gated research preview with access prioritized for defensive cybersecurity use cases
/// </summary>
[AspireValue("FoundryModels")]
public static readonly FoundryModel ClaudeMythos5 = new() { Name = "claude-mythos-5", Version = "1", Format = "Anthropic" };
/// <summary>
/// Claude Mythos Preview (gated research preview) is a new class of intelligence for cybersecurity, coding, and long-running agents. Only available as a gated research preview with access prioritized for defensive cybersecurity use cases
/// </summary>
[AspireValue("FoundryModels")]
public static readonly FoundryModel ClaudeMythosPreview = new() { Name = "claude-mythos-preview", Version = "1", Format = "Anthropic" };
/// <summary>
/// Claude Opus 4.5 is Anthropic’s most intelligent model, and an industry leader across coding, agents, computer use, and enterprise workflows. With a 200K token context window and 64K max output, Opus 4.5 is ideal for production code, sophisticated agents, o
/// </summary>
[AspireValue("FoundryModels")]
public static readonly FoundryModel ClaudeOpus45 = new() { Name = "claude-opus-4-5", Version = "20251101", Format = "Anthropic" };
/// <summary>
/// Claude Opus 4.6 is the latest version of Anthropic's most intelligent model, and the world's best model for coding, enterprise agents, and professional work. With a 1M token context window and 128K max output, Opus 4.6 is ideal for production code, sophist
/// </summary>
[AspireValue("FoundryModels")]
public static readonly FoundryModel ClaudeOpus46 = new() { Name = "claude-opus-4-6", Version = "1", Format = "Anthropic" };
/// <summary>
/// Claude Opus 4.7 is our most capable generally available model, advancing performance across coding, enterprise workflows, and long-running agentic tasks.
/// </summary>
[AspireValue("FoundryModels")]
public static readonly FoundryModel ClaudeOpus47 = new() { Name = "claude-opus-4-7", Version = "1", Format = "Anthropic" };
/// <summary>
/// Claude Opus 4.8 is our most intelligent Opus model and the best generally available model for coding and agents, with deeper reasoning for enterprise workflows.
/// </summary>
[AspireValue("FoundryModels")]
public static readonly FoundryModel ClaudeOpus48 = new() { Name = "claude-opus-4-8", Version = "2", Format = "Anthropic" };
/// <summary>
/// Claude Opus 5 is Anthropic's most advanced Opus model, powering long-running agents while delivering improvements in coding and professional work. It brings near-Fable intelligence to the model teams rely on daily for long-horizon coding and complex agenti
/// </summary>
[AspireValue("FoundryModels")]
public static readonly FoundryModel ClaudeOpus5 = new() { Name = "claude-opus-5", Version = "2", Format = "Anthropic" };
/// <summary>
/// Claude Sonnet 4.5 is Anthropic's most capable model for complex agents and an industry leader for coding and computer use.
/// </summary>
[AspireValue("FoundryModels")]
public static readonly FoundryModel ClaudeSonnet45 = new() { Name = "claude-sonnet-4-5", Version = "20250929", Format = "Anthropic" };
/// <summary>
/// Claude Sonnet 4.6 delivers frontier intelligence at scale—built for coding, agents, and enterprise workflows. With a 1M token context window and 128K max output, Sonnet 4.6 is ideal for coding, agents, office tasks, financial analysis, cybersecurity, and c
/// </summary>
[AspireValue("FoundryModels")]
public static readonly FoundryModel ClaudeSonnet46 = new() { Name = "claude-sonnet-4-6", Version = "1", Format = "Anthropic" };
/// <summary>
/// Claude Sonnet 5 is Anthropic's most capable Sonnet model yet, built for coding, agents, and professional work at scale. It brings near-Opus intelligence to the model teams run every day, with the same balance of capability, cost, and speed teams already re
/// </summary>
[AspireValue("FoundryModels")]
public static readonly FoundryModel ClaudeSonnet5 = new() { Name = "claude-sonnet-5", Version = "2", Format = "Anthropic" };
}
/// <summary>
/// Models published by Black Forest Labs.
/// </summary>
public static partial class BlackForestLabs
{
/// <summary>
/// Generate images with amazing image quality, prompt adherence, and diversity at blazing fast speeds. FLUX1.1 [pro] delivers six times faster image generation and achieved the highest Elo score on Artificial Analysis benchmarks when launched, surpassing all
/// </summary>
[AspireValue("FoundryModels")]
public static readonly FoundryModel Flux11Pro = new() { Name = "FLUX-1.1-pro", Version = "1", Format = "Black Forest Labs" };
/// <summary>
/// Generate and edit images through both text and image prompts. FLUX.1 Kontext is a multimodal flow matching model that enables both text-to-image generation and in-context image editing. Modify images while maintaining character consistency and performing l
/// </summary>
[AspireValue("FoundryModels")]
public static readonly FoundryModel Flux1KontextPro = new() { Name = "FLUX.1-Kontext-pro", Version = "1", Format = "Black Forest Labs" };
/// <summary>
/// Professional text-to-image generation with adjustable inference steps and guidance scale for fine-tuned control. Features superior typography and text rendering, supports up to 4MP resolution, 32K prompt tokens, and up to 8 reference images. Ideal for deve
/// </summary>
[AspireValue("FoundryModels")]
public static readonly FoundryModel Flux2Flex = new() { Name = "FLUX.2-flex", Version = "1", Format = "Black Forest Labs" };
/// <summary>
/// Generate and edit images through both text and image prompts. FLUX.2-pro is a multimodal flow matching model that enables both text-to-image generation and in-context image editing. Modify images while maintaining character consistency and performing local
/// </summary>
[AspireValue("FoundryModels")]
public static readonly FoundryModel Flux2Pro = new() { Name = "FLUX.2-pro", Version = "1", Format = "Black Forest Labs" };
}
/// <summary>
/// Models published by Cohere.
/// </summary>
public static partial class Cohere
{
/// <summary>
/// Command A is a highly efficient generative model that excels at agentic and multilingual use cases.
/// </summary>
[AspireValue("FoundryModels")]
public static readonly FoundryModel CohereCommandA = new() { Name = "cohere-command-a", Version = "4", Format = "Cohere" };
/// <summary>
/// Command A is a highly efficient generative model that excels at agentic and multilingual use cases.
/// </summary>
[AspireValue("FoundryModels")]
public static readonly FoundryModel CohereCommandAPlus052026 = new() { Name = "Cohere-command-a-plus-05-2026", Version = "1", Format = "Cohere" };
/// <summary>
/// Cohere Embed English is the market's leading text representation model used for semantic search, retrieval-augmented generation (RAG), classification, and clustering.
/// </summary>
[AspireValue("FoundryModels")]
public static readonly FoundryModel CohereEmbedV3English = new() { Name = "Cohere-embed-v3-english", Version = "1", Format = "Cohere" };
/// <summary>
/// Cohere Embed Multilingual is the market's leading text representation model used for semantic search, retrieval-augmented generation (RAG), classification, and clustering.
/// </summary>
[AspireValue("FoundryModels")]
public static readonly FoundryModel CohereEmbedV3Multilingual = new() { Name = "Cohere-embed-v3-multilingual", Version = "1", Format = "Cohere" };
/// <summary>
/// Rerank improves search systems by sorting documents based on their semantic similarity to a query
/// </summary>
[AspireValue("FoundryModels")]
public static readonly FoundryModel CohereRerankV40Fast = new() { Name = "Cohere-rerank-v4.0-fast", Version = "2", Format = "Cohere" };
/// <summary>
/// Rerank improves search systems by sorting documents based on their semantic similarity to a query
/// </summary>
[AspireValue("FoundryModels")]
public static readonly FoundryModel CohereRerankV40Pro = new() { Name = "Cohere-rerank-v4.0-pro", Version = "1", Format = "Cohere" };
/// <summary>
/// Embed 4 transforms texts and images into numerical vectors
/// </summary>
[AspireValue("FoundryModels")]
public static readonly FoundryModel EmbedV40 = new() { Name = "embed-v-4-0", Version = "6", Format = "Cohere" };
}
/// <summary>
/// Models published by DeepSeek.
/// </summary>
public static partial class DeepSeek
{
/// <summary>
/// DeepSeek-R1 excels at reasoning tasks using a step-by-step training process, such as language, scientific reasoning, and coding tasks.
/// </summary>
[AspireValue("FoundryModels")]
public static readonly FoundryModel DeepSeekR1 = new() { Name = "DeepSeek-R1", Version = "1", Format = "DeepSeek" };
/// <summary>
/// The DeepSeek R1 0528 model has improved reasoning capabilities, this version also offers a reduced hallucination rate, enhanced support for function calling, and better experience for vibe coding.
/// </summary>
[AspireValue("FoundryModels")]
public static readonly FoundryModel DeepSeekR10528 = new() { Name = "DeepSeek-R1-0528", Version = "1", Format = "DeepSeek" };
/// <summary>
/// DeepSeek-V3.2, a model that harmonizes high computational efficiency with superior reasoning and agent performance
/// </summary>
[AspireValue("FoundryModels")]
public static readonly FoundryModel DeepSeekV32 = new() { Name = "DeepSeek-V3.2", Version = "1", Format = "DeepSeek" };
/// <summary>
/// DeepSeek-V3.2 Speciale, a model that harmonizes high computational efficiency with superior reasoning and agent performance
/// </summary>
[AspireValue("FoundryModels")]
public static readonly FoundryModel DeepSeekV32Speciale = new() { Name = "DeepSeek-V3.2-Speciale", Version = "1", Format = "DeepSeek" };
/// <summary>
/// DeepSeek V4 is an efficient MoE model family with 1M context and near state-of-the-art open-source reasoning performance.
/// </summary>
[AspireValue("FoundryModels")]
public static readonly FoundryModel DeepSeekV4Flash = new() { Name = "DeepSeek-V4-Flash", Version = "2026-04-23", Format = "DeepSeek" };
/// <summary>
/// DeepSeek-V4-Flash-0731 is the official release of DeepSeek-V4-Flash, superseding the preview version, with substantially enhanced agentic capabilities.
/// </summary>
[AspireValue("FoundryModels")]
public static readonly FoundryModel DeepSeekV4Flash0731 = new() { Name = "DeepSeek-V4-Flash-0731", Version = "2026-07-31", Format = "DeepSeek" };
/// <summary>
/// DeepSeek V4 is an efficient MoE model family with 1M context and near state-of-the-art open-source reasoning performance.
/// </summary>
[AspireValue("FoundryModels")]
public static readonly FoundryModel DeepSeekV4Pro = new() { Name = "DeepSeek-V4-Pro", Version = "2026-04-23", Format = "DeepSeek" };
}
/// <summary>
/// Models published by Meta.
/// </summary>
public static partial class Meta
{
/// <summary>
/// Excels in image reasoning capabilities on high-res images for visual understanding apps.
/// </summary>
[AspireValue("FoundryModels")]
public static readonly FoundryModel Llama3211BVisionInstruct = new() { Name = "Llama-3.2-11B-Vision-Instruct", Version = "6", Format = "Meta" };
/// <summary>
/// Advanced image reasoning capabilities for visual understanding agentic apps.
/// </summary>
[AspireValue("FoundryModels")]
public static readonly FoundryModel Llama3290BVisionInstruct = new() { Name = "Llama-3.2-90B-Vision-Instruct", Version = "5", Format = "Meta" };
/// <summary>
/// Llama 3.3 70B Instruct offers enhanced reasoning, math, and instruction following with performance comparable to Llama 3.1 405B.
/// </summary>
[AspireValue("FoundryModels")]
public static readonly FoundryModel Llama3370BInstruct = new() { Name = "Llama-3.3-70B-Instruct", Version = "10", Format = "Meta" };
/// <summary>
/// Llama 4 Maverick 17B 128E Instruct FP8 is great at precise image understanding and creative writing, offering high quality at a lower price compared to Llama 3.3 70B
/// </summary>
[AspireValue("FoundryModels")]
public static readonly FoundryModel Llama4Maverick17B128EInstructFP8 = new() { Name = "Llama-4-Maverick-17B-128E-Instruct-FP8", Version = "5", Format = "Meta" };
/// <summary>
/// Llama 4 Scout 17B 16E Instruct is great at multi-document summarization, parsing extensive user activity for personalized tasks, and reasoning over vast codebases.
/// </summary>
[AspireValue("FoundryModels")]
public static readonly FoundryModel Llama4Scout17B16EInstruct = new() { Name = "Llama-4-Scout-17B-16E-Instruct", Version = "4", Format = "Meta" };
/// <summary>
/// The Llama 3.1 instruction tuned text only models are optimized for multilingual dialogue use cases and outperform many of the available open source and closed chat models on common industry benchmarks.
/// </summary>
[AspireValue("FoundryModels")]
public static readonly FoundryModel MetaLlama31405BInstruct = new() { Name = "Meta-Llama-3.1-405B-Instruct", Version = "1", Format = "Meta" };
/// <summary>
/// The Llama 3.1 instruction tuned text only models are optimized for multilingual dialogue use cases and outperform many of the available open source and closed chat models on common industry benchmarks.
/// </summary>
[AspireValue("FoundryModels")]
public static readonly FoundryModel MetaLlama318BInstruct = new() { Name = "Meta-Llama-3.1-8B-Instruct", Version = "6", Format = "Meta" };
}
/// <summary>
/// Models published by Microsoft.
/// </summary>
public static partial class Microsoft
{
/// <summary>
/// <para>
/// <b>Azure AI Content Safety</b>
/// </para>
/// <para>
/// <b>Introduction</b>
/// </para>
/// <para>Azure AI Content Safety is a safety system for monitoring content generated by both foundation models and humans. Detect and block potential risks, threats, and quality problems. You can build an advanced safety system for foundation models to detect and mitigate harmful content and risks in user prompts and AI-generated outputs. Use Prompt Shields to detect and block prompt injection attacks, groundedness detection to pinpoint ungrounded or hallucinated materials, and protected material detection to identify copyrighted or owned content.</para>
/// <para>
/// <b>Core Features</b>
/// </para>
/// <list type="bullet">
/// <item>
/// <description>
/// <para>
/// <b>Block harmful input and output</b>
/// </para>
/// <list type="bullet">
/// <item>
/// <description>
/// <para>
/// <b>Description</b>: Detect and block violence, hate, sexual, and self-harm content for both text, images and multimodal. Configure severity thresholds for your specific use case and adhere to your responsible AI policies.</para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>
/// <b>Key Features</b>: Violence, hate, sexual, and self-harm content detection. Custom blocklist.</para>
/// </description>
/// </item>
/// </list>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>
/// <b>Policy customization with custom categories</b>
/// </para>
/// <list type="bullet">
/// <item>
/// <description>
/// <para>
/// <b>Description</b>: Create unique content filters tailored to your requirements using custom categories. Quickly train a new custom category by providing examples of content you need to block.</para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>
/// <b>Key Features</b>: Custom categories</para>
/// </description>
/// </item>
/// </list>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>
/// <b>Identify the security risks</b>
/// </para>
/// <list type="bullet">
/// <item>
/// <description>
/// <para>
/// <b>Description</b>: Safeguard your AI applications against prompt injection attacks and jailbreak attempts. Identify and mitigate both direct and indirect threats with prompt shields.</para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>
/// <b>Key Features</b>: Direct jailbreak attack, indirect prompt injection from docs.</para>
/// </description>
/// </item>
/// </list>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>
/// <b>Detect and correct Gen AI hallucinations</b>
/// </para>
/// <list type="bullet">
/// <item>
/// <description>
/// <para>
/// <b>Description</b>: Identify and correct generative AI hallucinations and ensure outputs are reliable, accurate, and grounded in data with groundedness detection.</para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>
/// <b>Key Features</b>: Groundedness detection, reasoning, and correction.</para>
/// </description>
/// </item>
/// </list>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>
/// <b>Identify protected material</b>
/// </para>
/// <list type="bullet">
/// <item>
/// <description>
/// <para>
/// <b>Description</b>: Pinpoint copyrighted content and provide sources for preexisting text and code with protected material detection.</para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>
/// <b>Key Features</b>: Protected material for code, protected material for text</para>
/// </description>
/// </item>
/// </list>
/// </description>
/// </item>
/// </list>
/// <para>
/// <b>Use Cases</b>
/// </para>
/// <list type="bullet">
/// <item>
/// <description>
/// <para>Generative AI services screen user-submitted prompts and generated outputs to ensure safe and appropriate content.</para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>Online marketplaces monitor and filter product listings and other user-generated content to prevent harmful or inappropriate material.</para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>Gaming platforms manage and moderate user-created game content and in-game communication to maintain a safe environment.</para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>Social media platforms review and regulate user-uploaded images and posts to enforce community standards and prevent harmful content.</para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>Enterprise media companies implement centralized content moderation systems to ensure the safety and appropriateness of their published materials.</para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>K-12 educational technology providers filter out potentially harmful or inappropriate content to create a safe learning environment for students and educators.</para>
/// </description>
/// </item>
/// </list>
/// <para>
/// <b>Benefits</b>
/// </para>
/// <list type="bullet">
/// <item>
/// <description>
/// <para>
/// <b>No ML experience required</b>: Incorporate content safety features into your projects with no machine learning experience required.</para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>
/// <b>Effortlessly customize your RAI policies</b>: Customizing your content safety classifiers can be done with one line of description, a few samples using Custom Categories.</para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>
/// <b>State of the art models</b>: ready for use APIs, SOTA models, and flexible deployment options reduce the need for ongoing manual training or extensive customization. Microsoft has a science team and policy experts working on the frontier of Gen AI to constantly improve the safety and security models to ensure our customers can develop and deploy generative AI safely and responsibly.</para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>
/// <b>Global Reach</b>: Support more than 100 languages, enabling businesses to communicate effectively with customers, partners, and employees worldwide.</para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>
/// <b>Scalable and Reliable</b>: Built on Azure's cloud infrastructure, the Azure AI Content Safety service scales automatically to meet demand, from small business applications to global enterprise workloads.</para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>
/// <b>Security and Compliance</b>: Azure AI Content Safety runs on Azure's secure cloud infrastructure, ensuring data privacy and compliance with global standards. User data is not stored after the translation process.</para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>
/// <b>Flexible deployment</b>: Azure AI Content Safety can be deployed on cloud, on premises and on devices.</para>
/// </description>
/// </item>
/// </list>
/// <para>
/// <b>Technical Details</b>
/// </para>
/// <list type="bullet">
/// <item>
/// <description>
/// <para>
/// <b>Deployment</b>
/// </para>
/// <list type="bullet">
/// <item>
/// <description>
/// <para>
/// <b>Container for on-premise deployment</b>: <see href="https://learn.microsoft.com/azure/ai-services/content-safety/how-to/containers/container-overview">Content safety containers overview - Azure AI Content Safety - Azure AI services | Microsoft Learn</see></para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>
/// <b>Embedded Content Safety</b>: <see href="https://learn.microsoft.com/azure/ai-services/content-safety/how-to/embedded-content-safety?tabs=windows-target%2Ctext">Embedded Content Safety - Azure AI Content Safety - Azure AI services | Microsoft Learn</see></para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>
/// <b>Cloud</b>: <see href="https://learn.microsoft.com/azure/ai-services/content-safety/">Azure AI Content Safety documentation - Quickstarts, Tutorials, API Reference - Azure AI services | Microsoft Learn</see></para>
/// </description>
/// </item>
/// </list>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>
/// <b>Requirements</b>: Requirements vary feature by feature, for more details, refer to the Azure AI Content Safety documentation: <see href="https://learn.microsoft.com/azure/ai-services/content-safety/">Azure AI Content Safety documentation - Quickstarts, Tutorials, API Reference - Azure AI services | Microsoft Learn</see>.</para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>
/// <b>Support</b>: Azure AI Content Safety is part of Azure AI Services. Support options for AI Services can be found here: <see href="https://learn.microsoft.com/azure/ai-services/cognitive-services-support-options?context=%2Fazure%2Fai-services%2Fcontent-safety%2Fcontext%2Fcontext">Azure AI services support and help options - Azure AI services | Microsoft Learn</see>.</para>
/// </description>
/// </item>
/// </list>
/// <para>
/// <b>Pricing</b>
/// </para>
/// <para>Explore pricing options here: <see href="https://azure.microsoft.com/pricing/details/cognitive-services/content-safety/">Azure AI Content Safety - Pricing | Microsoft Azure</see>.</para>
/// </summary>
[AspireValue("FoundryModels")]
public static readonly FoundryModel AzureAIContentSafety = new() { Name = "Azure-AI-Content-Safety", Version = "1", Format = "Microsoft" };
/// <summary>
/// <para>
/// <b>Azure AI Content Understanding</b>
/// </para>
/// <para>
/// <b>Introduction</b>
/// </para>
/// <para>Azure AI Content Understanding empowers you to transform unstructured multimodal data—such as text, images, audio, and video—into structured, actionable insights. By streamlining content processing with advanced AI techniques like schema extraction and grounding, it delivers accurate structured data for downstream applications. Offering prebuilt templates for common use cases and customizable models, it helps you unify diverse data types into a single, efficient pipeline, optimizing workflows and accelerating time to value.</para>
/// <para>
/// <b>Core Features</b>
/// </para>
/// <list type="bullet">
/// <item>
/// <description>
/// <para>
/// <b>Multimodal data ingestion</b>
/// <br />Ingest a range of modalities such as documents, images, audio, or video. Use a variety of AI models to convert the input data into a structured format that can be easily processed and analyzed by downstream services or applications.</para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>
/// <b>Customizable output schemas</b>
/// <br />Customize the schemas of extracted results to meet your specific needs. Tailor the format and structure of summaries, insights, or features to include only the most relevant details—such as key points or timestamps—from video or audio files.</para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>
/// <b>Confidence scores</b> Leverage confidence scores to minimize human intervention and continuously improve accuracy through user feedback.</para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>
/// <b>Output ready for downstream applications</b>
/// <br />Automate business processes by building enterprise AI apps or agentic workflows. Use outputs that downstream applications can consume for reasoning with retrieval-augmented generation (RAG).</para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>
/// <b>Grounding</b> Ensure the information extracted, inferred, or abstracted is represented in the underlying content.</para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>
/// <b>Automatic labeling</b> Save time and effort on manual annotation and create models quicker by using large language models (LLMs) to extract fields from various document types.</para>
/// </description>
/// </item>
/// </list>
/// <para>
/// <b>Use Cases</b>
/// </para>
/// <list type="bullet">
/// <item>
/// <description>
/// <para>
/// <b>Post-call analytics for call centers</b>: Generate insights from call recordings, track key performance indicators (KPIs), and answer customer questions more accurately and efficiently.</para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>
/// <b>Tax process automation</b>: Streamline the tax return process by extracting data from tax forms to create a consolidated view of information across various documents.</para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>
/// <b>Media asset management</b>: Extract features from images and videos to provide richer tools for targeted content and enhance media asset management solutions.</para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>
/// <b>Chart understanding</b>: Enhance chart understanding by automating the analysis and interpretation of various types of charts and diagrams using Content Understanding.</para>
/// </description>
/// </item>
/// </list>
/// <para>
/// <b>Benefits</b>
/// </para>
/// <list type="bullet">
/// <item>
/// <description>
/// <para>
/// <b>Streamline workflows</b>: Azure AI Content Understanding standardizes the extraction of content, structure, and insights from various content types into a unified process.</para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>
/// <b>Simplify field extraction</b>: Field extraction in Content Understanding makes it easier to generate structured output from unstructured content. Define a schema to extract, classify, or generate field values with no complex prompt engineering.</para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>
/// <b>Enhance accuracy</b>: Content Understanding employs multiple AI models to analyze and cross-validate information simultaneously, resulting in more accurate and reliable results.</para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>
/// <b>Confidence scores & grounding</b>: Content Understanding ensures the accuracy of extracted values while minimizing the cost of human review.</para>
/// </description>
/// </item>
/// </list>
/// <para>
/// <b>Technical Details</b>
/// </para>
/// <list type="bullet">
/// <item>
/// <description>
/// <para>
/// <b>Deployment</b>: Deployment options may vary by service, reference the following docs for more information: <see href="https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/how-to/create-multi-service-resource">Create a Microsoft Foundry resource</see>.</para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>
/// <b>Requirements</b>: Requirements may vary depending on the input data you are analyzing, reference the following docs for more information: <see href="https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/service-limits">Service quotas and limits</see>.</para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>
/// <b>Support</b>: Support options for AI Services can be found here: <see href="https://learn.microsoft.com/en-us/azure/ai-services/cognitive-services-support-options?view=doc-intel-4.0.0">Azure AI services support and help options</see>.</para>
/// </description>
/// </item>
/// </list>
/// <para>
/// <b>Pricing</b>
/// </para>
/// <para>View up-to-date pay-as-you-go pricing details here: <see href="https://azure.microsoft.com/en-us/pricing/details/content-understanding/">Azure AI Content Understanding pricing</see>.</para>
/// </summary>
[AspireValue("FoundryModels")]
public static readonly FoundryModel AzureAIContentUnderstanding = new() { Name = "Azure-AI-Content-Understanding", Version = "1", Format = "Microsoft" };
/// <summary>
/// <para>
/// <b>Azure AI Document Intelligence</b>
/// </para>
/// <para>Document Intelligence is a cloud-based service that enables you to build intelligent document processing solutions. Massive amounts of data, spanning a wide variety of data types, are stored in forms and documents. Document Intelligence enables you to effectively manage the velocity at which data is collected and processed and is key to improved operations, informed data-driven decisions, and enlightened innovation.</para>
/// <para>
/// <b>Core Features</b>
/// </para>
/// <list type="bullet">
/// <item>
/// <description>
/// <para>
/// <b>General extraction models</b>
/// </para>
/// <list type="bullet">
/// <item>
/// <description>
/// <para>
/// <b>Description</b>: General extraction models enable text extraction from forms and documents and return structured business-ready content ready for your organization's action, use, or development.</para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>
/// <b>Key Features</b>
/// </para>
/// <list type="bullet">
/// <item>
/// <description>
/// <para>Read model allows you to extract written or printed text liens, words, locations, and detected languages.</para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>Layout model, on top of text extraction, extracts structural information like tables, selection marks, paragraphs, titles, headings, and subheadings. Layout model can also output the extraction results in a Markdown format, enabling you to define your semantic chunking strategy based on provided building blocks, allowing for easier RAG (Retrieval Augmented Generation).</para>
/// </description>
/// </item>
/// </list>
/// </description>
/// </item>
/// </list>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>
/// <b>Prebuilt models</b>
/// </para>
/// <list type="bullet">
/// <item>
/// <description>
/// <para>
/// <b>Description</b>: Prebuilt models enable you to add intelligent document processing to your apps and flows without having to train and build your own models. Prebuilt models extract a pre-defined set of fields depending on the document type.</para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>
/// <b>Key Features</b>
/// </para>
/// <list type="bullet">
/// <item>
/// <description>
/// <para>
/// <b>Financial Services and Legal Documents</b>: Credit Cards, Bank Statement, Pay Slip, Check, Invoices, Receipts, Contracts.</para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>
/// <b>US Tax Documents</b>: Unified Tax, W-2, 1099 Combo, 1040 (multiple variations), 1098 (multiple variations), 1099 (multiple variations).</para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>
/// <b>US Mortgage Documents</b>: 1003, 1004, 1005, 1008, Closing Disclosure.</para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>
/// <b>Personal Identification Documents</b>: Identity Documents, Health Insurance Cards, Marriage Certificates.</para>
/// </description>
/// </item>
/// </list>
/// </description>
/// </item>
/// </list>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>
/// <b>Custom models</b>
/// </para>
/// <list type="bullet">
/// <item>
/// <description>
/// <para>
/// <b>Description</b>: Custom models are trained using your labeled datasets to extract distinct data from forms and documents, specific to your use cases. Standalone custom models can be combined to create composed models.</para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>
/// <b>Key Features</b>
/// </para>
/// <list type="bullet">
/// <item>
/// <description>
/// <para>
/// <b>Document field extraction models</b>
/// </para>
/// <list type="bullet">
/// <item>
/// <description>
/// <para>
/// <b>Custom generative</b>: Build a custom extraction model using generative AI for documents with unstructured format and varying templates.</para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>
/// <b>Custom neural</b>: Extract data from mixed-type documents.</para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>
/// <b>Custom template</b>: Extract data from static layouts.</para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>
/// <b>Custom composed</b>: Extract data using a collection of models. Explicitly choose the classifier and enable confidence-based routing based on the threshold you set.</para>
/// </description>
/// </item>
/// </list>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>
/// <b>Custom classification models</b>
/// </para>
/// <list type="bullet">
/// <item>
/// <description>
/// <para>
/// <b>Custom classifier</b>: Identify designated document types (classes) before invoking an extraction model.</para>
/// </description>
/// </item>
/// </list>
/// </description>
/// </item>
/// </list>
/// </description>
/// </item>
/// </list>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>
/// <b>Add-on capabilities</b>
/// </para>
/// <list type="bullet">
/// <item>
/// <description>
/// <para>
/// <b>Description</b>: Use the add-on features to extend the results to include more features extracted from your documents. Some add-on features incur an extra cost. These optional features can be enabled and disabled depending on the scenario of the document extraction.</para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>
/// <b>Key Features</b>
/// </para>
/// <list type="bullet">
/// <item>
/// <description>
/// <para>High resolution extraction</para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>Formula extraction</para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>Font extraction</para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>Barcode extraction</para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>Language detection</para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>Searchable PDF output</para>
/// </description>
/// </item>
/// </list>
/// </description>
/// </item>
/// </list>
/// </description>
/// </item>
/// </list>
/// <para>
/// <b>Use Cases</b>
/// </para>
/// <list type="bullet">
/// <item>
/// <description>
/// <para>
/// <b>Accounts payable</b>: A company can increase the efficiency of its accounts payable clerks by using the prebuilt invoice model and custom forms to speed up invoice data entry with a human in the loop. The prebuilt invoice model can extract key fields, such as Invoice Total and Shipping Address.</para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>
/// <b>Insurance form processing</b>: A customer can train a model by using custom forms to extract a key-value pair in insurance forms and then feeds the data to their business flow to improve the accuracy and efficiency of their process. For their unique forms, customers can build their own model that extracts key values by using custom forms. These extracted values then become actionable data for various workflows within their business.</para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>
/// <b>Bank form processing</b>: A bank can use the prebuilt ID model and custom forms to speed up the data entry for "know your customer" documentation, or to speed up data entry for a mortgage packet. If a bank requires their customers to submit personal identification as part of a process, the prebuilt ID model can extract key values, such as Name and Document Number, speeding up the overall time for data entry.</para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>
/// <b>Robotic process automation (RPA)</b>: Using the custom extraction model, customers can extract specific data needed from distinct types of documents. The key-value pair extracted can then be entered into various systems such as databases, or CRM systems, through RPA, replacing manual data entry. Customers can also use custom classification model to categorize documents based on their content and file them in proper location. As such, an organized set of data extracted from the custom model can be an essential first step to document RPA scenarios for businesses that manage large volumes of documents regularly.</para>
/// </description>
/// </item>
/// </list>
/// <para>
/// <b>Benefits</b>
/// </para>
/// <list type="bullet">
/// <item>
/// <description>
/// <para>
/// <b>No experience required</b>: Incorporate Document Intelligence features into your projects with no machine learning experience required.</para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>
/// <b>Effortlessly customize your models</b>: Training your own custom extraction and classification model can be done with as little as one document labeled, making it easy to train your own models.</para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>
/// <b>State of the art models</b>: ready for use APIs, constantly enhanced models, and flexible deployment options reduce the need for ongoing manual training or extensive customization.</para>
/// </description>
/// </item>
/// </list>
/// <para>
/// <b>Technical Details:</b>
/// </para>
/// <list type="bullet">
/// <item>
/// <description>
/// <para>
/// <b>Deployment</b>: Deployment options may vary by service, reference the following docs for more information: <see href="https://learn.microsoft.com/azure/ai-services/document-intelligence/how-to-guides/use-sdk-rest-api?view=doc-intel-3.1.0&tabs=linux&pivots=programming-language-rest-api">Use Document Intelligence models</see> and <see href="https://learn.microsoft.com/azure/ai-services/document-intelligence/containers/install-run?view=doc-intel-4.0.0&tabs=read">Install and run containers</see>.</para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>
/// <b>Requirements</b>: Requirements may vary slightly depending on the model you are using to analyze the documents. Reference the following docs for more information: <see href="https://learn.microsoft.com/azure/ai-services/document-intelligence/service-limits?view=doc-intel-4.0.0">Service quotas and limits</see>.</para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>
/// <b>Support</b>: Support options for AI Services can be found here: <see href="https://learn.microsoft.com/azure/ai-services/cognitive-services-support-options?context=%2Fazure%2Fai-services%2Fdocument-intelligence%2Fcontext%2Fcontext&view=doc-intel-4.0.0">Azure AI services support and help options - Azure AI services | Microsoft Learn</see>.</para>
/// </description>
/// </item>
/// </list>
/// <para>
/// <b>Pricing</b>
/// </para>
/// <para>View up-to-date pricing information for the pay-as-you-go pricing model here: <see href="https://azure.microsoft.com/pricing/details/ai-document-intelligence/">Azure AI Document Intelligence pricing</see>.</para>
/// </summary>
[AspireValue("FoundryModels")]
public static readonly FoundryModel AzureAIDocumentIntelligence = new() { Name = "Azure-AI-Document-Intelligence", Version = "1", Format = "Microsoft" };
/// <summary>
/// <para>
/// <b>Azure AI Vision</b>
/// </para>
/// <para>
/// <b>Introduction</b>
/// </para>
/// <para>The Azure AI Vision service gives you access to advanced algorithms that process images and videos and return insights based on the visual features and content you are interested in. Azure AI Vision can power a diverse set of scenarios, including digital asset management, video content search & summary, identity verification, generating accessible alt-text for images, and many more. The key product categories for Azure AI Vision include Video Analysis, Image Analysis, Face, and Optical Character Recognition.</para>
/// <para>
/// <b>Core Features</b>
/// </para>
/// <list type="bullet">
/// <item>
/// <description>
/// <para>
/// <b>Video analysis</b>
/// </para>
/// <list type="bullet">
/// <item>
/// <description>
/// <para>
/// <b>Description</b>: Video Analysis includes video-related features like Spatial Analysis and Video Retrieval. Spatial Analysis analyzes the presence and movement of people on a video feed and produces events that other systems can respond to. Video Retrieval lets you create an index of videos that you can search in your natural language.</para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>
/// <b>Key Features</b>: Video retrieval, spatial analysis, person counting, person in a zone, person crossing a line, person distance</para>
/// </description>
/// </item>
/// </list>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>
/// <b>Face</b>
/// </para>
/// <list type="bullet">
/// <item>
/// <description>
/// <para>
/// <b>Description</b>: The Face service provides AI algorithms that detect, recognize, and analyze human faces in images. Facial recognition software is important in many different scenarios, such as identification, touchless access control, and face blurring for privacy.</para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>
/// <b>Key Features</b>: Face detection and analysis, face liveness, face identification, face verification</para>
/// </description>
/// </item>
/// </list>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>
/// <b>Image analysis</b>
/// </para>
/// <list type="bullet">
/// <item>
/// <description>
/// <para>
/// <b>Description</b>: The Image Analysis service extracts many visual features from images, such as objects, faces, adult content, and auto-generated text descriptions.</para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>
/// <b>Key Features</b>: Image tagging, image classification, object detection, image captioning, dense captioning, face detection, optical character recognition, image embeddings, and image search</para>
/// </description>
/// </item>
/// </list>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>
/// <b>Optical character recognition</b>
/// </para>
/// <list type="bullet">
/// <item>
/// <description>
/// <para>
/// <b>Description</b>: The Optical Character Recognition (OCR) service extracts text from images. You can use the Read API to extract printed and handwritten text from photos and documents. It uses deep-learning-based models and works with text on various surfaces and backgrounds. These include business documents, invoices, receipts, posters, business cards, letters, and whiteboards. The OCR APIs support extracting printed text in several languages.</para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>
/// <b>Key Features</b>: OCR</para>
/// </description>
/// </item>
/// </list>
/// </description>
/// </item>
/// </list>
/// <para>
/// <b>Use Cases</b>
/// </para>
/// <list type="bullet">
/// <item>
/// <description>
/// <para>Boost content discovery with image analysis</para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>Verify identities with the Face service</para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>Search content in videos</para>
/// </description>
/// </item>
/// </list>
/// <para>
/// <b>Benefits</b>
/// </para>
/// <list type="bullet">
/// <item>
/// <description>
/// <para>
/// <b>No experience required</b>: Incorporate vision features into your projects with no machine learning experience required.</para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>
/// <b>Effortlessly customize your models</b>: Customizing your image classification and object detection models can be done with as little as one image per tag, making it easy to train your own models.</para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>
/// <b>State of the art models</b>: Ready to use APIs, constantly enhanced models, and flexible deployment options reduce the need for ongoing manual training or extensive customization.</para>
/// </description>
/// </item>
/// </list>
/// <para>
/// <b>Technical Details</b>
/// </para>
/// <list type="bullet">
/// <item>
/// <description>
/// <para>
/// <b>Deployment</b>: Deployment options may vary by service, reference the following docs for more information: <see href="https://learn.microsoft.com/azure/ai-services/computer-vision/overview-image-analysis?tabs=4-0">Image Analysis Overview</see>, <see href="https://learn.microsoft.com/azure/ai-services/computer-vision/overview-ocr">Optical Character Recognition Overview</see>, <see href="https://learn.microsoft.com/azure/ai-services/computer-vision/intro-to-spatial-analysis-public-preview?tabs=sa">Video Analysis Overview</see>, and <see href="https://learn.microsoft.com/azure/ai-services/computer-vision/overview-identity">Face Overview</see>.</para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>
/// <b>Requirements</b>: Requirements may very slightly depending on the data you are analyzing, reference the following docs for more information: <see href="https://learn.microsoft.com/azure/ai-services/computer-vision/overview-image-analysis?tabs=4-0">Image Analysis Overview</see>, <see href="https://learn.microsoft.com/azure/ai-services/computer-vision/overview-ocr">Optical Character Recognition Overview</see>, <see href="https://learn.microsoft.com/azure/ai-services/computer-vision/intro-to-spatial-analysis-public-preview?tabs=sa">Video Analysis Overview</see>, and <see href="https://learn.microsoft.com/azure/ai-services/computer-vision/overview-identity">Face Overview</see>.</para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>
/// <b>Support</b>: Support options for AI Services can be found here: <see href="https://learn.microsoft.com/azure/ai-services/cognitive-services-support-options?context=%2Fazure%2Fai-services%2Fcomputer-vision%2Fcontext%2Fcontext">Azure AI services support and help options - Azure AI services | Microsoft Learn</see>.</para>
/// </description>
/// </item>
/// </list>
/// <para>
/// <b>Pricing</b>
/// </para>
/// <para>View up-to-date pricing information for the pay-as-you-go pricing model here: <see href="https://azure.microsoft.com/pricing/details/cognitive-services/computer-vision">Azure AI Vision pricing</see>.</para>
/// </summary>
[AspireValue("FoundryModels")]
public static readonly FoundryModel AzureAIVision = new() { Name = "Azure-AI-Vision", Version = "1", Format = "Microsoft" };
/// <summary>
/// <para>
/// <b>Azure Content Understanding - Layout</b>
/// </para>
/// <para>Content Understanding Layout offers rich, structure‑aware extraction that captures text, formatting, tables, figures, and geometric layout details. It’s designed for complex document understanding workflows that require positional accuracy and deeper structural insights.</para>
/// <para>
/// <b>Azure Content Understanding</b>
/// </para>
/// <para>Azure Content Understanding uses generative AI to process/ingest content of many types (documents, images, videos, and audio) into a user-defined output format. It offers a streamlined process to reason over large amounts of unstructured data, accelerating time-to-value by generating an output that can be integrated into automation and analytical workflows.</para>
/// <para>
/// <b>Key capabilities</b>
/// </para>
/// <para>
/// <b>About this model</b>
/// </para>
/// <para>The <b>Layout</b> model offers rich, structure‑aware analysis for documents that require deeper understanding of formatting, hierarchy, and spatial relationships. It combines textual extraction with geometric layout detection to support advanced automation and content reasoning.</para>
/// <para>
/// <b>Key model capabilities</b>
/// </para>
/// <list type="bullet">
/// <item>
/// <description>
/// <para>Extracts detailed content and layout elements such as <b>words</b>, <b>paragraphs</b>, <b>tables</b>, <b>figures</b>, and <b>sections</b></para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>Identifies <b>document structure</b>, formatting patterns, and hierarchical organization</para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>Extracts <b>hyperlinks</b> embedded in documents</para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>Captures <b>annotations</b> such as highlights, underlines, and strikethroughs in digital PDFs</para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>Provides <b>precise positional information</b> for all extracted elements</para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>Detects all figure types—<b>charts</b>, <b>diagrams</b>, <b>pictures</b>, <b>icons</b>, and other images—with bounding box details (<b>PDF only</b>)</para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>Suitable for advanced workflows such as <b>document automation</b>, <b>RAG indexing</b>, <b>semantic</b> search, and any process demanding fine‑grained layout understanding</para>
/// </description>
/// </item>
/// </list>
/// <para>
/// <b>Pricing</b>
/// </para>
/// <para>View up-to-date pay-as-you-go pricing details here: <see href="https://azure.microsoft.com/en-us/pricing/details/content-understanding/">Azure AI Content Understanding pricing</see>.</para>
/// <para>
/// <b>Technical details</b>
/// </para>
/// <list type="bullet">
/// <item>
/// <description>
/// <para>
/// <b>Deployment</b>: Deployment options may vary by service, reference the following docs for more information: <see href="https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/how-to/create-multi-service-resource">Create a Microsoft Foundry resource</see>.</para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>
/// <b>Requirements</b>: Requirements may vary depending on the input data you are analyzing, reference the following docs for more information: <see href="https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/service-limits">Service quotas and limits</see>.</para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>
/// <b>Support</b>: Support options for AI Services can be found here: <see href="https://learn.microsoft.com/en-us/azure/ai-services/cognitive-services-support-options?view=doc-intel-4.0.0">Azure AI services support and help options</see>.</para>
/// </description>
/// </item>
/// </list>
/// <para>
/// <b>More information</b>
/// </para>
/// <para>Learn more in the full <see href="https://aka.ms/content-understanding-doc">Azure AI Content Understanding documentation</see>.</para>
/// </summary>
[AspireValue("FoundryModels")]
public static readonly FoundryModel AzureContentUnderstandingLayout = new() { Name = "Azure-Content-Understanding-Layout", Version = "1", Format = "Microsoft" };
/// <summary>
/// <para>
/// <b>Azure Content Understanding - Read</b>
/// </para>
/// <para>Content Understanding Read provides fast, reliable extraction of text and basic content elements from documents, enabling simple ingestion workflows without layout interpretation. It’s ideal for scenarios where clean text output is needed for downstream automation, classification, or search.</para>
/// <para>
/// <b>Azure Content Understanding</b>
/// </para>
/// <para>Azure Content Understanding uses generative AI to process/ingest content of many types (documents, images, videos, and audio) into a user-defined output format. It offers a streamlined process to reason over large amounts of unstructured data, accelerating time-to-value by generating an output that can be integrated into automation and analytical workflows.</para>
/// <para>
/// <b>Key capabilities</b>
/// </para>
/// <para>
/// <b>About this model</b>
/// </para>
/// <para>The <b>Read</b> model provides foundational text extraction capabilities for simple, fast, and reliable ingestion of document content. It focuses on capturing textual elements without performing layout or structural analysis, making it ideal for lightweight processing and downstream text-based workflows.</para>
/// <para>
/// <b>Key model capabilities</b>
/// </para>
/// <list type="bullet">
/// <item>
/// <description>
/// <para>Extracts fundamental content elements such as <b>words</b>, <b>lines</b>, <b>paragraphs</b>, <b>formulas</b>, and <b>barcodes</b></para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>Provides <b>basic OCR</b> functionality for a wide range of document types</para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>Returns text results <b>without layout interpretation</b></para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>Best suited for scenarios requiring <b>quick ingestion</b>, metadata extraction, transcription, or feeding clean text into analytic or search pipelines</para>
/// </description>
/// </item>
/// </list>
/// <para>
/// <b>Pricing</b>
/// </para>
/// <para>View up-to-date pay-as-you-go pricing details here: <see href="https://azure.microsoft.com/en-us/pricing/details/content-understanding/">Azure AI Content Understanding pricing</see>.</para>
/// <para>
/// <b>Technical details</b>
/// </para>
/// <list type="bullet">
/// <item>
/// <description>
/// <para>
/// <b>Deployment</b>: Deployment options may vary by service, reference the following docs for more information: <see href="https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/how-to/create-multi-service-resource">Create a Microsoft Foundry resource</see>.</para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>
/// <b>Requirements</b>: Requirements may vary depending on the input data you are analyzing, reference the following docs for more information: <see href="https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/service-limits">Service quotas and limits</see>.</para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>
/// <b>Support</b>: Support options for AI Services can be found here: <see href="https://learn.microsoft.com/en-us/azure/ai-services/cognitive-services-support-options?view=doc-intel-4.0.0">Azure AI services support and help options</see>.</para>
/// </description>
/// </item>
/// </list>
/// <para>
/// <b>More information</b>
/// </para>
/// <para>Learn more in the full <see href="https://aka.ms/content-understanding-doc">Azure AI Content Understanding documentation</see>.</para>
/// </summary>
[AspireValue("FoundryModels")]
public static readonly FoundryModel AzureContentUnderstandingRead = new() { Name = "Azure-Content-Understanding-Read", Version = "1", Format = "Microsoft" };
/// <summary>
/// PII Redaction for Conversation automatically detects and masks sensitive information such as names, addresses, phone numbers, credit card details, and other personally identifiable information (PII) in meeting transcripts.
/// </summary>
[AspireValue("FoundryModels")]
public static readonly FoundryModel AzureLanguageConversationalPiiRedaction = new() { Name = "Azure-Language-Conversational-PII-redaction", Version = "1", Format = "Microsoft" };
/// <summary>
/// PII Redaction for Documents automatically detects and masks sensitive information such as names, addresses, phone numbers, credit card details, and other personally identifiable information (PII) in native documents including PDF, Word, and text files.
/// </summary>
[AspireValue("FoundryModels")]
public static readonly FoundryModel AzureLanguageDocumentPiiRedaction = new() { Name = "Azure-Language-Document-PII-redaction", Version = "1", Format = "Microsoft" };
/// <summary>
/// Language detection quickly and accurately identifies the language of any text, supporting over 100 languages and dialects, including the ISO 15924 standard for a select number of languages.
/// </summary>
[AspireValue("FoundryModels")]
public static readonly FoundryModel AzureLanguageLanguageDetection = new() { Name = "Azure-Language-Language-detection", Version = "1", Format = "Microsoft" };
/// <summary>
/// Text Analytics for Health extracts and labels relevant medical information from unstructured clinical text, including doctors' notes, discharge summaries, and electronic health records, using named entity recognition, relation extraction, entity linking, a
/// </summary>
[AspireValue("FoundryModels")]
public static readonly FoundryModel AzureLanguageTextAnalyticsForHealth = new() { Name = "Azure-Language-Text-Analytics-for-Health", Version = "1", Format = "Microsoft" };
/// <summary>
/// PII Redaction for Text automatically detects and masks sensitive information such as names, addresses, phone numbers, credit card details, and other personally identifiable information (PII) in unstructured text.
/// </summary>
[AspireValue("FoundryModels")]
public static readonly FoundryModel AzureLanguageTextPiiRedaction = new() { Name = "Azure-Language-Text-PII-redaction", Version = "1", Format = "Microsoft" };
/// <summary>
/// Transcribes streaming or recorded audio into readable text across 140+ languages and dialects. Accuracy can be further optimized with custom models for your specialized use cases.
/// </summary>
[AspireValue("FoundryModels")]
public static readonly FoundryModel AzureSpeechSpeechToText = new() { Name = "Azure-Speech-Speech-to-text", Version = "1", Format = "Microsoft" };
/// <summary>
/// Translates streaming or recorded audio into text or audio across 140+ languages and dialects. Accuracy can be further optimized with custom models for your specialized use cases.
/// </summary>
[AspireValue("FoundryModels")]
public static readonly FoundryModel AzureSpeechSpeechTranslation = new() { Name = "Azure-Speech-Speech-Translation", Version = "1", Format = "Microsoft" };
/// <summary>
/// <para>Text-to-speech enables your applications, tools, or devices to convert text into natural synthesized speech. It leverages advanced out-of-the-box [prebuilt neural voices](<see href="https://learn.microsoft.com/en-us/azure/ai-services/speech-service/language-support?t">https://learn.microsoft.com/en-us/azure/ai-services/speech-service/language-support?t</see></para>
/// </summary>
[AspireValue("FoundryModels")]
public static readonly FoundryModel AzureSpeechTextToSpeech = new() { Name = "Azure-Speech-Text-to-speech", Version = "1", Format = "Microsoft" };
/// <summary>
/// Text to speech avatar converts text into a digital video of a human (either a standard avatar or a custom text to speech avatar) speaking with a natural-sounding voice. The text to speech avatar video can be synthesized asynchronously or in real time. Deve
/// </summary>
[AspireValue("FoundryModels")]
public static readonly FoundryModel AzureSpeechTextToSpeechAvatar = new() { Name = "Azure-Speech-Text-to-speech-Avatar", Version = "1", Format = "Microsoft" };
/// <summary>
/// Voice Live API is a single unified API that enables low-latency, high-quality speech to speech interactions for voice agents.
/// </summary>
[AspireValue("FoundryModels")]
public static readonly FoundryModel AzureSpeechVoiceLive = new() { Name = "Azure-Speech-Voice-Live", Version = "1", Format = "Microsoft" };
/// <summary>
/// Document translation is a cloud-based, multilingual service that uses AI to translate documents from one language to another while preserving the document layout.
/// </summary>
[AspireValue("FoundryModels")]
public static readonly FoundryModel AzureTranslatorDocumentTranslation = new() { Name = "Azure-Translator-Document-translation", Version = "1", Format = "Microsoft" };
/// <summary>
/// Text translation is a cloud-based, multilingual service that uses neural machine translation models (NMT) and/or large language models (LLM) to translate text from one language to another, supporting 135 languages.
/// </summary>
[AspireValue("FoundryModels")]
public static readonly FoundryModel AzureTranslatorTextTranslation = new() { Name = "Azure-Translator-Text-translation", Version = "1", Format = "Microsoft" };
/// <summary>
/// MAI-Transcribe-1 is an ASR model built to deliver high quality batch transcription whenever the user speaks. It is designed to achieve high accuracy across 25 languages and to adapt seamlessly to diverse accents, dialects, and regional speech patterns.
/// </summary>
[AspireValue("FoundryModels")]
public static readonly FoundryModel MaiTranscribe1 = new() { Name = "MAI-Transcribe-1", Version = "2026-01-23", Format = "Microsoft" };
/// <summary>
/// MAI-Transcribe-1.5 is the second iteration of Microsoft's best-in-class speech-to-text model family. It delivers consistently strong transcription accuracy across 43 languages, accents, speaking styles, and noisy environments, with faster inference and now
/// </summary>
[AspireValue("FoundryModels")]
public static readonly FoundryModel MaiTranscribe15 = new() { Name = "MAI-Transcribe-1.5", Version = "2026-06-02", Format = "Microsoft" };
/// <summary>
/// MAI-Voice-1 is a text-to-speech (TTS) model that generates high-quality single-speaker speech and, soon, multi-speaker speech for public preview. It produces audio that strictly follows the input transcript and supports per-turn emotion control as well as
/// </summary>
[AspireValue("FoundryModels")]
public static readonly FoundryModel MaiVoice1 = new() { Name = "MAI-Voice-1", Version = "2025-12-18", Format = "Microsoft" };
/// <summary>
/// MAI-Voice-2 is a prompted text-to-speech (TTS) model that generates high-fidelity, natural, and expressive speech across 10+ languages. It captures human-like intonation, rhythm, and emotional nuance for engaging conversational experiences.
/// </summary>
[AspireValue("FoundryModels")]
public static readonly FoundryModel MaiVoice2 = new() { Name = "MAI-Voice-2", Version = "2026-06-02", Format = "Microsoft" };
/// <summary>
/// MAI-Voice-2-Flash is a text-to-speech (TTS) model built for ultra-fast, low-latency generation. It delivers high-fidelity, natural, and expressive speech across 15 languages, while being optimized for real-time responsiveness for voice agents, assistants,
/// </summary>
[AspireValue("FoundryModels")]
public static readonly FoundryModel MaiVoice2Flash = new() { Name = "MAI-Voice-2-Flash", Version = "2026-07-22", Format = "Microsoft" };
/// <summary>
/// Model router is a deployable AI model that is trained to select the most suitable large language model (LLM) for a given prompt.
/// </summary>
[AspireValue("FoundryModels")]
public static readonly FoundryModel ModelRouter = new() { Name = "model-router", Version = "2025-11-18", Format = "Microsoft" };
/// <summary>
/// A 7B parameters model, proves better quality than Phi-3-mini, with a focus on high-quality, reasoning-dense data.
/// </summary>
[AspireValue("FoundryModels")]
public static readonly FoundryModel Phi3Small8kInstruct = new() { Name = "Phi-3-small-8k-instruct", Version = "6", Format = "Microsoft" };
/// <summary>
/// <para>
/// <b>Model Summary</b>
/// </para>
/// <para>Phi-3 Vision is a lightweight, state-of-the-art open multimodal model built upon datasets which include - synthetic data and filtered publicly available websites - with a focus on very high-quality, reasoning dense data both on text and vision. The model belongs to the Phi-3 model family, and the multimodal version comes with 128K context length (in tokens) it can support. The model underwent a rigorous enhancement process, incorporating both supervised fine-tuning and direct preference optimization to ensure precise instruction adherence and robust safety measures.</para>
/// <para>Resources and Technical Documentation:</para>
/// <list type="bullet">
/// <item>
/// <description>
/// <para>
/// <see href="https://aka.ms/phi3blog-april">Phi-3 Microsoft Blog</see>
/// </para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>
/// <see href="https://aka.ms/phi3-tech-report">Phi-3 Technical Report</see>
/// </para>
/// </description>
/// </item>
/// </list>
/// <para>
/// <b>Training</b>
/// </para>
/// <para>
/// <b>Model</b>
/// </para>
/// <list type="bullet">
/// <item>
/// <description>
/// <para>Architecture: Phi-3-Vision-128K-Instruct has 4.2B parameters and contains image encoder, connector, projector, and Phi-3 Mini language model.</para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>Inputs: Text and Image. It’s best suited for prompts using the chat format.</para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>Context length: 128K tokens</para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>GPUs: 512 H100-80G</para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>Training time: 1.5 days</para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>Training data: 500B vision and text tokens</para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>Outputs: Generated text in response to the input</para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>Dates: Our models were trained between February and April 2024</para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>Status: This is a static model trained on an offline text dataset with cutoff date Mar 15, 2024. Future versions of the tuned models may be released as we improve models.</para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>Release Type: Open weight release</para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>Release dates: The model weight is released on May 21, 2024.</para>
/// </description>
/// </item>
/// </list>
/// <para>
/// <b>Datasets</b>
/// </para>
/// <para>Our training data includes a wide variety of sources, and is a combination of</para>
/// <list type="number">
/// <item>
/// <description>
/// <para>publicly available documents filtered rigorously for quality, selected high-quality educational data and code;</para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>selected high-quality image-text interleave;</para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>newly created synthetic, “textbook-like” data for the purpose of teaching math, coding, common sense reasoning, general knowledge of the world (science, daily activities, theory of mind, etc.), newly created image data, e.g., chart/table/diagram/slides;</para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>high quality chat format supervised data covering various topics to reflect human preferences on different aspects such as instruct-following, truthfulness, honesty and helpfulness.</para>
/// </description>
/// </item>
/// </list>
/// <para>The data collection process involved sourcing information from publicly available documents, with a meticulous approach to filtering out undesirable documents and images. To safeguard privacy, we carefully filtered various image and text data sources to remove or scrub any potentially personal data from the training data.</para>
/// <para>More details can be found in the <see href="https://aka.ms/phi3-tech-report">Phi-3 Technical Report</see>.</para>
/// <para>
/// <b>Benchmarks</b>
/// </para>
/// <para>To understand the capabilities, we compare Phi-3 Vision-128K-Instruct with a set of models over a variety of zero-shot benchmarks using our internal benchmark platform.</para>
/// <para> </para>
/// <para>Benchmark</para>
/// <para>Phi-3 Vision-128K-In1</para>
/// <para>LlaVA-1.6 Vicuna-7B</para>
/// <para>QWEN-VL Chat</para>
/// <para>Llama3-Llava-Next-8B</para>
/// <para>Claude-3 Haiku</para>
/// <para>Gemini 1.0 Pro V</para>
/// <para>GPT-4V-Turbo</para>
/// <para>MMMU</para>
/// <para>40.4</para>
/// <para>34.2</para>
/// <para>39.0</para>
/// <para>36.4</para>
/// <para>40.7</para>
/// <para>42.0</para>
/// <para>55.5</para>
/// <para>MMBench</para>
/// <para>80.5</para>
/// <para>76.3</para>
/// <para>75.8</para>
/// <para>79.4</para>
/// <para>62.4</para>
/// <para>80.0</para>
/// <para>86.1</para>
/// <para>ScienceQA</para>
/// <para>90.8</para>
/// <para>70.6</para>
/// <para>67.2</para>
/// <para>73.7</para>
/// <para>72.0</para>
/// <para>79.7</para>
/// <para>75.7</para>
/// <para>MathVista</para>
/// <para>44.5</para>
/// <para>31.5</para>
/// <para>29.4</para>
/// <para>34.8</para>
/// <para>33.2</para>
/// <para>35.0</para>
/// <para>47.5</para>
/// <para>InterGPS</para>
/// <para>38.1</para>
/// <para>20.5</para>
/// <para>22.3</para>
/// <para>24.6</para>
/// <para>32.1</para>
/// <para>28.6</para>
/// <para>41.0</para>
/// <para>AI2D</para>
/// <para>76.7</para>
/// <para>63.1</para>
/// <para>59.8</para>
/// <para>66.9</para>
/// <para>60.3</para>
/// <para>62.8</para>
/// <para>74.7</para>
/// <para>ChartQA</para>
/// <para>81.4</para>
/// <para>55.0</para>
/// <para>50.9</para>
/// <para>65.8</para>
/// <para>59.3</para>
/// <para>58.0</para>
/// <para>62.3</para>
/// <para>TextVQA</para>
/// <para>70.9</para>
/// <para>64.6</para>
/// <para>59.4</para>
/// <para>55.7</para>
/// <para>62.7</para>
/// <para>64.7</para>
/// <para>68.1</para>
/// <para>POPE</para>
/// <para>85.8</para>
/// <para>87.2</para>
/// <para>82.6</para>
/// <para>87.0</para>
/// <para>74.4</para>
/// <para>84.2</para>
/// <para>83.7</para>
/// <para>
/// <b>Intended Uses</b>
/// </para>
/// <para>
/// <b>Primary use cases</b>
/// </para>
/// <para>The model is intended for broad commercial and research use in English. The model provides uses for general purpose AI systems and applications with visual and text input capabilities which require</para>
/// <list type="number">
/// <item>
/// <description>
/// <para>memory/compute constrained environments;</para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>latency bound scenarios;</para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>general image understanding;</para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>OCR;</para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>chart and table understanding.</para>
/// </description>
/// </item>
/// </list>
/// <para>The model is designed to accelerate research on efficient language and multimodal models, for use as a building block for generative AI powered features.</para>
/// <para>
/// <b>Use case considerations</b>
/// </para>
/// <para>The model is not specifically designed or evaluated for all downstream purposes. Developers should consider common limitations of language models as they select use cases, and evaluate and mitigate for accuracy, safety, and fairness before using within a specific downstream use case, particularly for high-risk scenarios. Developers should be aware of and adhere to applicable laws or regulations (including privacy, trade compliance laws, etc.) that are relevant to their use case.</para>
/// <para>Nothing contained in this Model Card should be interpreted as or deemed a restriction or modification to the license the model is released under.</para>
/// <para>
/// <b>Responsible AI Considerations</b>
/// </para>
/// <para>Like other models, the Phi family of models can potentially behave in ways that are unfair, unreliable, or offensive. Some of the limiting behaviors to be aware of include:</para>
/// <list type="bullet">
/// <item>
/// <description>
/// <para>Quality of Service: The Phi models are trained primarily on English text. Languages other than English will experience worse performance English language varieties with less representation in the training data might experience worse performance than standard American English.</para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>Representation of Harms & Perpetuation of Stereotypes: These models can over- or under-represent groups of people, erase representation of some groups, or reinforce demeaning or negative stereotypes. Despite safety post-training, these limitations may still be present due to differing levels of representation of different groups or prevalence of examples of negative stereotypes in training data that reflect real-world patterns and societal biases.</para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>Inappropriate or Offensive Content: These models may produce other types of inappropriate or offensive content, which may make it inappropriate to deploy for sensitive contexts without additional mitigations that are specific to the use case.</para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>Information Reliability: Language models can generate nonsensical content or fabricate content that might sound reasonable but is inaccurate or outdated.</para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>Limited Scope for Code: Majority of Phi-3 training data is based in Python and use common packages such as "typing, math, random, collections, datetime, itertools". If the model generates Python scripts that utilize other packages or scripts in other languages, we strongly recommend users manually verify all API uses.</para>
/// </description>
/// </item>
/// </list>
/// <para>Developers should apply responsible AI best practices and are responsible for ensuring that a specific use case complies with relevant laws and regulations (e.g. privacy, trade, etc.). Important areas for consideration include:</para>
/// <list type="bullet">
/// <item>
/// <description>
/// <para>Allocation: Models may not be suitable for scenarios that could have consequential impact on legal status or the allocation of resources or life opportunities (ex: housing, employment, credit, etc.) without further assessments and additional debiasing techniques.</para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>High-Risk Scenarios: Developers should assess suitability of using models in high-risk scenarios where unfair, unreliable or offensive outputs might be extremely costly or lead to harm. This includes providing advice in sensitive or expert domains where accuracy and reliability are critical (ex: legal or health advice). Additional safeguards should be implemented at the application level according to the deployment context.</para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>Misinformation: Models may produce inaccurate information. Developers should follow transparency best practices and inform end-users they are interacting with an AI system. At the application level, developers can build feedback mechanisms and pipelines to ground responses in use-case specific, contextual information, a technique known as Retrieval Augmented Generation (RAG).</para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>Generation of Harmful Content: Developers should assess outputs for their context and use available safety classifiers or custom solutions appropriate for their use case.</para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>Misuse: Other forms of misuse such as fraud, spam, or malware production may be possible, and developers should ensure that their applications do not violate applicable laws and regulations.</para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>Identification of individuals: models with vision capabilities may have the potential to uniquely identify individuals in images. Safety post-training steers the model to refuse such requests, but developers should consider and implement, as appropriate, additional mitigations or user consent flows as required in their respective jurisdiction, (e.g., building measures to blur faces in image inputs before processing).</para>
/// </description>
/// </item>
/// </list>
/// <para>
/// <b>Inference Samples</b>
/// </para>
/// <para>Inference type</para>
/// <para>Python sample (Notebook)</para>
/// <para>CLI with YAML</para>
/// <para>Real time</para>
/// <para>
/// <see href="https://aka.ms/azureml-infer-sdk-image-text-to-text-generation">image-text-to-text-generation-online-endpoint.ipynb</see>image-text-to-text-generation-online-endpoint.ipynb</para>
/// <para>
/// <see href="https://aka.ms/azureml-infer-cli-image-text-to-text-generation">image-text-to-text-generation-online-endpoint.sh</see>image-text-to-text-generation-online-endpoint.sh</para>
/// <para>
/// <b>Sample inputs and outputs (for real-time inference)</b>
/// </para>
/// <para>Phi-3-vision model only supports single image per conversation. Specifically, please refer to below grid:</para>
/// <para />
/// <para>Single-turn</para>
/// <para>Multi-turn conversation</para>
/// <para>Single Image</para>
/// <para>Yes</para>
/// <para>Yes</para>
/// <para>Multiple Images</para>
/// <para>No</para>
/// <para>No</para>
/// <para>
/// <b>Sample Input</b>
/// </para>
/// <code>
/// {
/// "input_data": {
/// "input_string": [
/// {
/// "role": "user",
/// "content": [
/// {
/// "type": "image_url",
/// "image_url": {
/// "url": "https://www.ilankelman.org/stopsigns/australia.jpg"
/// }
/// },
/// {
/// "type": "text",
/// "text": "What is shown in this image? Be extremely detailed and specific."
/// }
/// ]
/// }
/// ],
/// "parameters": { "temperature": 0.7, "max_new_tokens": 2048 }
/// }
/// }</code>
/// <para>
/// <b>Sample Output</b>
/// </para>
/// <code>
/// {
/// "output": " The image captures a vibrant street scene. Dominating the left side of the image is a red stop sign, standing on a white pole. Adjacent to the stop sign, a white lion statue adds a touch of symbolism to the scene. \n\nThe background is filled with colorful buildings, including a red one and a yellow one, adding a lively atmosphere to the scene. The blue sky overhead and a clear white road underneath it complete the picture. \n\nAdding to the cultural context, there are Chinese characters visible in the background, suggesting the presence of a Chinese influence in this location. The overall scene is a blend of urban life and cultural elements."
///
/// }</code>
/// <para>
/// <b>Software</b>
/// </para>
/// <list type="bullet">
/// <item>
/// <description>
/// <para>
/// <see href="https://github.com/pytorch/pytorch">PyTorch</see>
/// </para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>
/// <see href="https://github.com/huggingface/transformers">Transformers</see>
/// </para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>
/// <see href="https://github.com/HazyResearch/flash-attention">Flash-Attention</see>
/// </para>
/// </description>
/// </item>
/// </list>
/// <para>
/// <b>Hardware</b>
/// </para>
/// <para>Note that by default, the Phi-3-Vision-128K model uses flash attention, which requires certain types of GPU hardware to run. We have tested on the following GPU types:</para>
/// <list type="bullet">
/// <item>
/// <description>
/// <para>NVIDIA A100</para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>NVIDIA A6000</para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>NVIDIA H100</para>
/// </description>
/// </item>
/// </list>
/// <para>
/// <b>License</b>
/// </para>
/// <para>The model is licensed under the MIT license.</para>
/// <para>
/// <b>Trademarks</b>
/// </para>
/// <para>This project may contain trademarks or logos for projects, products, or services. Authorized use of Microsoft trademarks or logos is subject to and must follow <see href="https://www.microsoft.com/en-us/legal/intellectualproperty/trademarks">Microsoft’s Trademark & Brand Guidelines</see>. Use of Microsoft trademarks or logos in modified versions of this project must not cause confusion or imply Microsoft sponsorship. Any use of third-party trademarks or logos are subject to those third-party’s policies.</para>
/// </summary>
[AspireValue("FoundryModels")]
public static readonly FoundryModel Phi3Vision128kInstruct = new() { Name = "Phi-3-vision-128k-instruct", Version = "2", Format = "Microsoft" };
/// <summary>
/// Phi-4 14B, a highly capable model for low latency scenarios.
/// </summary>
[AspireValue("FoundryModels")]
public static readonly FoundryModel Phi4 = new() { Name = "Phi-4", Version = "7", Format = "Microsoft" };
/// <summary>
/// 3.8B parameters Small Language Model outperforming larger models in reasoning, math, coding, and function-calling
/// </summary>
[AspireValue("FoundryModels")]
public static readonly FoundryModel Phi4MiniInstruct = new() { Name = "Phi-4-mini-instruct", Version = "1", Format = "Microsoft" };
/// <summary>
/// Lightweight math reasoning model optimized for multi-step problem solving
/// </summary>
[AspireValue("FoundryModels")]
public static readonly FoundryModel Phi4MiniReasoning = new() { Name = "Phi-4-mini-reasoning", Version = "1", Format = "Microsoft" };
/// <summary>
/// First small multimodal model to have 3 modality inputs (text, audio, image), excelling in quality and efficiency
/// </summary>
[AspireValue("FoundryModels")]
public static readonly FoundryModel Phi4MultimodalInstruct = new() { Name = "Phi-4-multimodal-instruct", Version = "2", Format = "Microsoft" };
/// <summary>
/// State-of-the-art open-weight reasoning model.
/// </summary>
[AspireValue("FoundryModels")]
public static readonly FoundryModel Phi4Reasoning = new() { Name = "Phi-4-reasoning", Version = "1", Format = "Microsoft" };
}
/// <summary>
/// Models published by Mistral AI.
/// </summary>
public static partial class MistralAI
{
/// <summary>
/// Codestral 25.01 by Mistral AI is designed for code generation, supporting 80+ programming languages, and optimized for tasks like code completion and fill-in-the-middle
/// </summary>
[AspireValue("FoundryModels")]
public static readonly FoundryModel Codestral2501 = new() { Name = "Codestral-2501", Version = "2", Format = "Mistral AI" };
/// <summary>
/// Ministral 3B is a state-of-the-art Small Language Model (SLM) optimized for edge computing and on-device applications. As it is designed for low-latency and compute-efficient inference, it it also the perfect model for standard GenAI applications that have
/// </summary>
[AspireValue("FoundryModels")]
public static readonly FoundryModel Ministral3B = new() { Name = "Ministral-3B", Version = "1", Format = "Mistral AI" };
/// <summary>
/// Document conversion to markdown with interleaved images and text
/// </summary>
[AspireValue("FoundryModels")]
public static readonly FoundryModel MistralDocumentAi2512 = new() { Name = "mistral-document-ai-2512", Version = "1", Format = "Mistral AI" };
/// <summary>
/// Mistral Large 3 is a state-of-the-art General-purpose Multimodal granular Mixture-of-Experts model with 39B active parameters, 673B total parameters featuring 128 experts per layer and Multi-Latent attention.
/// </summary>
[AspireValue("FoundryModels")]
public static readonly FoundryModel MistralLarge3 = new() { Name = "Mistral-Large-3", Version = "1", Format = "Mistral AI" };
/// <summary>
/// Mistral Medium 3 is an advanced Large Language Model (LLM) with state-of-the-art reasoning, knowledge, coding and vision capabilities.
/// </summary>
[AspireValue("FoundryModels")]
public static readonly FoundryModel MistralMedium2505 = new() { Name = "mistral-medium-2505", Version = "1", Format = "Mistral AI" };
/// <summary>
/// Mistral Medium 3.5 is our first "fully merged" model with enhanced code and agentic capabilities. It demonstrates strong tool dexterity, making it suitable for both VIP (Vibe Code Scaffold) and agentic research tasks.
/// </summary>
[AspireValue("FoundryModels")]
public static readonly FoundryModel MistralMedium35 = new() { Name = "mistral-medium-3-5", Version = "1", Format = "Mistral AI" };
/// <summary>
/// Document conversion to markdown with interleaved images and text
/// </summary>
[AspireValue("FoundryModels")]
public static readonly FoundryModel MistralOcr40 = new() { Name = "mistral-ocr-4-0", Version = "1", Format = "Mistral AI" };
/// <summary>
/// Enhanced Mistral Small 3 with multimodal capabilities and a 128k context length.
/// </summary>
[AspireValue("FoundryModels")]
public static readonly FoundryModel MistralSmall2503 = new() { Name = "mistral-small-2503", Version = "1", Format = "Mistral AI" };
}
/// <summary>
/// Models published by OpenAI.
/// </summary>
public static partial class OpenAI
{
/// <summary>
/// codex-mini is a fine-tuned variant of the o4-mini model, designed to deliver rapid, instruction-following performance for developers working in CLI workflows. Whether you're automating shell commands, editing scripts, or refactoring repositories, Codex-Min
/// </summary>
[AspireValue("FoundryModels")]
public static readonly FoundryModel CodexMini = new() { Name = "codex-mini", Version = "2025-05-16", Format = "OpenAI" };
/// <summary>
/// computer-use-preview is the model for Computer Use Agent for use in Responses API. You can use computer-use-preview model to get instructions to control a browser on your computer screen and take action on a user's behalf.
/// </summary>
[AspireValue("FoundryModels")]
public static readonly FoundryModel ComputerUsePreview = new() { Name = "computer-use-preview", Version = "2025-03-11", Format = "OpenAI" };
/// <summary>
/// <para>
/// <b>Azure Direct Models</b>
/// </para>
/// <para>Direct from Azure models are a select portfolio curated for their market-differentiated capabilities:</para>
/// <list type="bullet">
/// <item>
/// <description>
/// <para>Secure and managed by Microsoft: Purchase and manage models directly through Azure with a single license, consistent support, and no third-party dependencies, backed by Azure's enterprise-grade infrastructure.</para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>Streamlined operations: Benefit from unified billing, governance, and seamless PTU portability across models hosted on Azure - all as part of one Azure AI Foundry platform.</para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>Future-ready flexibility: Access the latest models as they become available, and easily test, deploy, or switch between them within Azure AI Foundry; reducing integration effort.</para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>Cost control and optimization: Scale on demand with pay-as-you-go flexibility or reserve PTUs for predictable performance and savings.</para>
/// </description>
/// </item>
/// </list>
/// <para>Learn more about <see href="https://aka.ms/DirectfromAzure">Direct from Azure models</see>.</para>
/// <para>
/// <b>Key capabilities</b>
/// </para>
/// <para>
/// <b>About this model</b>
/// </para>
/// <para>The provider has not supplied this information.</para>
/// <para>
/// <b>Key model capabilities</b>
/// </para>
/// <para>Davinci-002 supports fine-tuning, allowing developers and businesses to customize the model for specific applications.</para>
/// <para>
/// <b>Use cases</b>
/// </para>
/// <para>See Responsible AI for additional considerations for responsible use.</para>
/// <para>
/// <b>Key use cases</b>
/// </para>
/// <para>The provider has not supplied this information.</para>
/// <para>
/// <b>Out of scope use cases</b>
/// </para>
/// <para>The provider has not supplied this information.</para>
/// <para>
/// <b>Pricing</b>
/// </para>
/// <para>Pricing is based on a number of factors, including deployment type and tokens used. <see href="https://azure.microsoft.com/en-us/pricing/details/ai-foundry-models/microsoft/?msockid=1775f99b2f8e614e1ba1eb792e496067">See pricing details here.</see></para>
/// <para>
/// <b>Technical specs</b>
/// </para>
/// <para>The provider has not supplied this information.</para>
/// <para>
/// <b>Training cut-off date</b>
/// </para>
/// <para>This model supports 16384 max input tokens and training data is up to Sep 2021.</para>
/// <para>
/// <b>Training time</b>
/// </para>
/// <para>The provider has not supplied this information.</para>
/// <para>
/// <b>Input formats</b>
/// </para>
/// <para>Your training data and validation data sets consist of input and output examples for how you would like the model to perform. The training and validation data you use must be formatted as a JSON Lines (JSONL) document in which each line represents a single prompt-completion pair.</para>
/// <para>
/// <b>Output formats</b>
/// </para>
/// <para>The provider has not supplied this information.</para>
/// <para>
/// <b>Supported languages</b>
/// </para>
/// <para>The provider has not supplied this information.</para>
/// <para>
/// <b>Sample JSON response</b>
/// </para>
/// <para>The provider has not supplied this information.</para>
/// <para>
/// <b>Model architecture</b>
/// </para>
/// <para>Davinci-002 is the latest version of Davinci, a gpt-3 based model.</para>
/// <para>
/// <b>Long context</b>
/// </para>
/// <para>This model supports 16384 max input tokens.</para>
/// <para>
/// <b>Optimizing model performance</b>
/// </para>
/// <para>The provider has not supplied this information.</para>
/// <para>
/// <b>Additional assets</b>
/// </para>
/// <para>Learn more at https://learn.microsoft.com/azure/cognitive-services/openai/concepts/models</para>
/// <para>
/// <b>Training disclosure</b>
/// </para>
/// <para>
/// <b>Training, testing and validation</b>
/// </para>
/// <para>The provider has not supplied this information.</para>
/// <para>
/// <b>Distribution</b>
/// </para>
/// <para>
/// <b>Distribution channels</b>
/// </para>
/// <para>The provider has not supplied this information.</para>
/// <para>
/// <b>More information</b>
/// </para>
/// <para>The provider has not supplied this information.</para>
/// </summary>
[AspireValue("FoundryModels")]
public static readonly FoundryModel Davinci002 = new() { Name = "davinci-002", Version = "3", Format = "OpenAI" };
/// <summary>
/// gpt-4.1 outperforms gpt-4o across the board, with major gains in coding, instruction following, and long-context understanding
/// </summary>
[AspireValue("FoundryModels")]
public static readonly FoundryModel Gpt41 = new() { Name = "gpt-4.1", Version = "2025-04-14", Format = "OpenAI" };
/// <summary>
/// gpt-4.1-mini outperform gpt-4o-mini across the board, with major gains in coding, instruction following, and long-context handling
/// </summary>
[AspireValue("FoundryModels")]
public static readonly FoundryModel Gpt41Mini = new() { Name = "gpt-4.1-mini", Version = "2025-04-14", Format = "OpenAI" };
/// <summary>
/// gpt-4.1-nano provides gains in coding, instruction following, and long-context handling along with lower latency and cost
/// </summary>
[AspireValue("FoundryModels")]
public static readonly FoundryModel Gpt41Nano = new() { Name = "gpt-4.1-nano", Version = "2025-04-14", Format = "OpenAI" };
/// <summary>
/// OpenAI's most advanced multimodal model in the gpt-4o family. Can handle both text and image inputs.
/// </summary>
[AspireValue("FoundryModels")]
public static readonly FoundryModel Gpt4o = new() { Name = "gpt-4o", Version = "2024-11-20", Format = "OpenAI" };
/// <summary>
/// An affordable, efficient AI solution for diverse text and image tasks.
/// </summary>
[AspireValue("FoundryModels")]
public static readonly FoundryModel Gpt4oMini = new() { Name = "gpt-4o-mini", Version = "2024-07-18", Format = "OpenAI" };
/// <summary>
/// A highly efficient and cost effective speech-to-text solution that deliverables reliable and accurate transcripts.
/// </summary>
[AspireValue("FoundryModels")]
public static readonly FoundryModel Gpt4oMiniTranscribe = new() { Name = "gpt-4o-mini-transcribe", Version = "2025-12-15", Format = "OpenAI" };
/// <summary>
/// An advanced text-to-speech solution designed to convert written text into natural-sounding speech.
/// </summary>
[AspireValue("FoundryModels")]
public static readonly FoundryModel Gpt4oMiniTts = new() { Name = "gpt-4o-mini-tts", Version = "2025-12-15", Format = "OpenAI" };
/// <summary>
/// A cutting-edge speech-to-text solution that deliverables reliable and accurate transcripts.
/// </summary>
[AspireValue("FoundryModels")]
public static readonly FoundryModel Gpt4oTranscribe = new() { Name = "gpt-4o-transcribe", Version = "2025-03-20", Format = "OpenAI" };
/// <summary>
/// A cutting-edge speech-to-text solution that deliverables reliable and accurate transcripts; now equipped with diarization support aka identifying different speakers through the transcription.
/// </summary>
[AspireValue("FoundryModels")]
public static readonly FoundryModel Gpt4oTranscribeDiarize = new() { Name = "gpt-4o-transcribe-diarize", Version = "2025-10-15", Format = "OpenAI" };
/// <summary>
/// gpt-5 is designed for logic-heavy and multi-step tasks.
/// </summary>
[AspireValue("FoundryModels")]
public static readonly FoundryModel Gpt5 = new() { Name = "gpt-5", Version = "2025-08-07", Format = "OpenAI" };
/// <summary>
/// gpt-5-codex is designed for steerability, front end development, and interactivity.
/// </summary>
[AspireValue("FoundryModels")]
public static readonly FoundryModel Gpt5Codex = new() { Name = "gpt-5-codex", Version = "2025-09-15", Format = "OpenAI" };
/// <summary>
/// gpt-5-mini is a lightweight version for cost-sensitive applications.
/// </summary>
[AspireValue("FoundryModels")]
public static readonly FoundryModel Gpt5Mini = new() { Name = "gpt-5-mini", Version = "2025-08-07", Format = "OpenAI" };
/// <summary>
/// gpt-5-nano is optimized for speed, ideal for applications requiring low latency.
/// </summary>
[AspireValue("FoundryModels")]
public static readonly FoundryModel Gpt5Nano = new() { Name = "gpt-5-nano", Version = "2025-08-07", Format = "OpenAI" };
/// <summary>
/// gpt-5-pro uses more compute to think harder and provide consistently better answers.
/// </summary>
[AspireValue("FoundryModels")]
public static readonly FoundryModel Gpt5Pro = new() { Name = "gpt-5-pro", Version = "2025-10-06", Format = "OpenAI" };
/// <summary>
/// gpt-5.1 is designed for logic-heavy and multi-step tasks.
/// </summary>
[AspireValue("FoundryModels")]
public static readonly FoundryModel Gpt51 = new() { Name = "gpt-5.1", Version = "2025-11-13", Format = "OpenAI" };
/// <summary>
/// gpt-5.1-codex is designed for steerability, front end development, and interactivity.
/// </summary>
[AspireValue("FoundryModels")]
public static readonly FoundryModel Gpt51Codex = new() { Name = "gpt-5.1-codex", Version = "2025-11-13", Format = "OpenAI" };
/// <summary>
/// gpt-5.1-codex-max is agentic coding model designed to streamline complex development workflows with advanced efficiency
/// </summary>
[AspireValue("FoundryModels")]
public static readonly FoundryModel Gpt51CodexMax = new() { Name = "gpt-5.1-codex-max", Version = "2025-12-04", Format = "OpenAI" };
/// <summary>
/// gpt-5.1-codex-mini is designed for steerability, front end development, and interactivity.
/// </summary>
[AspireValue("FoundryModels")]
public static readonly FoundryModel Gpt51CodexMini = new() { Name = "gpt-5.1-codex-mini", Version = "2025-11-13", Format = "OpenAI" };
/// <summary>
/// GPT-5.2 is engineered for enterprise agent scenarios—delivering structured, auditable outputs, reliable tool use, and governed integrations.
/// </summary>
[AspireValue("FoundryModels")]
public static readonly FoundryModel Gpt52 = new() { Name = "gpt-5.2", Version = "2025-12-11", Format = "OpenAI" };
/// <summary>
/// gpt-5.2-codex is designed for steerability, front end development, and interactivity.
/// </summary>
[AspireValue("FoundryModels")]
public static readonly FoundryModel Gpt52Codex = new() { Name = "gpt-5.2-codex", Version = "2026-01-14", Format = "OpenAI" };
/// <summary>
/// gpt-5.3-codex is designed for steerability, front end development, and interactivity.
/// </summary>
[AspireValue("FoundryModels")]
public static readonly FoundryModel Gpt53Codex = new() { Name = "gpt-5.3-codex", Version = "2026-02-24", Format = "OpenAI" };
/// <summary>
/// GPT‑5.4 is OpenAI’s most capable frontier model, built to deliver faster, more reliable results for complex professional work.
/// </summary>
[AspireValue("FoundryModels")]
public static readonly FoundryModel Gpt54 = new() { Name = "gpt-5.4", Version = "2026-03-05", Format = "OpenAI" };
/// <summary>
/// GPT‑5.4‑mini is a compact, cost‑efficient model designed for reliable performance across high‑volume, everyday AI workloads.
/// </summary>
[AspireValue("FoundryModels")]
public static readonly FoundryModel Gpt54Mini = new() { Name = "gpt-5.4-mini", Version = "2026-03-17", Format = "OpenAI" };
/// <summary>
/// GPT‑5.4‑nano is a lightweight, ultra‑efficient model designed for low‑latency, cost‑effective tasks at massive scale.
/// </summary>
[AspireValue("FoundryModels")]
public static readonly FoundryModel Gpt54Nano = new() { Name = "gpt-5.4-nano", Version = "2026-03-17", Format = "OpenAI" };
/// <summary>
/// GPT‑5.4-Pro is OpenAI's most capable frontier model, built to deliver faster, more reliable results for complex professional work.
/// </summary>
[AspireValue("FoundryModels")]
public static readonly FoundryModel Gpt54Pro = new() { Name = "gpt-5.4-pro", Version = "2026-03-05", Format = "OpenAI" };
/// <summary>
/// GPT‑5.5 is OpenAI’s most capable frontier model, built to deliver faster, more reliable results for complex professional work.
/// </summary>
[AspireValue("FoundryModels")]
public static readonly FoundryModel Gpt55 = new() { Name = "gpt-5.5", Version = "2026-04-24", Format = "OpenAI" };
/// <summary>
/// GPT‑5.6-luna is OpenAI's most capable frontier model, built to deliver faster, more reliable results for complex professional work.
/// </summary>
[AspireValue("FoundryModels")]
public static readonly FoundryModel Gpt56Luna = new() { Name = "gpt-5.6-luna", Version = "2026-07-09", Format = "OpenAI" };
/// <summary>
/// GPT‑5.6-sol is OpenAI's most capable frontier model, built to deliver faster, more reliable results for complex professional work.
/// </summary>
[AspireValue("FoundryModels")]
public static readonly FoundryModel Gpt56Sol = new() { Name = "gpt-5.6-sol", Version = "2026-07-09", Format = "OpenAI" };
/// <summary>
/// GPT‑5.6-terra is OpenAI's most capable frontier model, built to deliver faster, more reliable results for complex professional work.
/// </summary>
[AspireValue("FoundryModels")]
public static readonly FoundryModel Gpt56Terra = new() { Name = "gpt-5.6-terra", Version = "2026-07-09", Format = "OpenAI" };
/// <summary>
/// Best suited for rich, asynchronous audio input/output interactions, such as creating spoken summaries from text.
/// </summary>
[AspireValue("FoundryModels")]
public static readonly FoundryModel GptAudio = new() { Name = "gpt-audio", Version = "2025-08-28", Format = "OpenAI" };
/// <summary>
/// A new S2S (speech to speech) model with improved instruction following.
/// </summary>
[AspireValue("FoundryModels")]
public static readonly FoundryModel GptAudio15 = new() { Name = "gpt-audio-1.5", Version = "2026-02-23", Format = "OpenAI" };
/// <summary>
/// Best suited for rich, asynchronous audio input/output interactions, such as creating spoken summaries from text.
/// </summary>
[AspireValue("FoundryModels")]
public static readonly FoundryModel GptAudioMini = new() { Name = "gpt-audio-mini", Version = "2025-10-06", Format = "OpenAI" };
/// <summary>
/// gpt-chat-latest (preview) is an advanced, natural, multimodal, and context-aware conversations for enterprise applications.
/// </summary>
[AspireValue("FoundryModels")]
public static readonly FoundryModel GptChatLatest = new() { Name = "gpt-chat-latest", Version = "2026-08-06", Format = "OpenAI" };
/// <summary>
/// An efficient AI solution for diverse text and image tasks, including high quality, cheap text to image generation
/// </summary>
[AspireValue("FoundryModels")]
public static readonly FoundryModel GptImage1Mini = new() { Name = "gpt-image-1-mini", Version = "2025-10-06", Format = "OpenAI" };
/// <summary>
/// An efficient AI solution for diverse text and image tasks, including high quality, and editing scenarios
/// </summary>
[AspireValue("FoundryModels")]
public static readonly FoundryModel GptImage15 = new() { Name = "gpt-image-1.5", Version = "2025-12-16", Format = "OpenAI" };
/// <summary>
/// An efficient AI solution for diverse text and image tasks, including high quality, and editing scenarios
/// </summary>
[AspireValue("FoundryModels")]
public static readonly FoundryModel GptImage2 = new() { Name = "gpt-image-2", Version = "2026-04-21", Format = "OpenAI" };
/// <summary>
/// A new real-time speech-to-text (STT) model with enhanced transcription accuracy and low-latency streaming capabilities.
/// </summary>
[AspireValue("FoundryModels")]
public static readonly FoundryModel GptLiveTranscribe = new() { Name = "gpt-live-transcribe", Version = "2026-07-28", Format = "OpenAI" };
/// <summary>
/// Push the open model frontier with GPT-OSS models, released under the permissive Apache 2.0 license, allowing anyone to use, modify, and deploy them freely.
/// </summary>
[AspireValue("FoundryModels")]
public static readonly FoundryModel GptOss120b = new() { Name = "gpt-oss-120b", Version = "4", Format = "OpenAI" };
/// <summary>
/// Push the open model frontier with GPT-OSS models, released under the permissive Apache 2.0 license, allowing anyone to use, modify, and deploy them freely.
/// </summary>
[AspireValue("FoundryModels")]
public static readonly FoundryModel GptOss20b = new() { Name = "gpt-oss-20b", Version = "11", Format = "OpenAI" };
/// <summary>
/// A new S2S (speech to speech) model with improved instruction following.
/// </summary>
[AspireValue("FoundryModels")]
public static readonly FoundryModel GptRealtime = new() { Name = "gpt-realtime", Version = "2025-08-28", Format = "OpenAI" };
/// <summary>
/// A new S2S (speech to speech) model with improved instruction following.
/// </summary>
[AspireValue("FoundryModels")]
public static readonly FoundryModel GptRealtime15 = new() { Name = "gpt-realtime-1.5", Version = "2026-02-23", Format = "OpenAI" };
/// <summary>
/// Gpt‑realtime‑2 is a next‑generation speech‑to‑speech reasoning model that processes live audio input and generates audio responses with built‑in reasoning, enabling low‑latency conversational voice interactions.
/// </summary>
[AspireValue("FoundryModels")]
public static readonly FoundryModel GptRealtime2 = new() { Name = "gpt-realtime-2", Version = "2026-05-07", Format = "OpenAI" };
/// <summary>
/// Gpt‑realtime‑2.1 is a next‑generation speech‑to‑speech reasoning model that processes live audio input and generates audio responses with built‑in reasoning, enabling low‑latency conversational voice interactions.
/// </summary>
[AspireValue("FoundryModels")]
public static readonly FoundryModel GptRealtime21 = new() { Name = "gpt-realtime-2.1", Version = "2026-07-07", Format = "OpenAI" };
/// <summary>
/// Gpt‑realtime‑2.1‑mini is a next‑generation speech‑to‑speech reasoning model that processes live audio input and generates audio responses with built‑in reasoning, enabling low‑latency conversational voice interactions.
/// </summary>
[AspireValue("FoundryModels")]
public static readonly FoundryModel GptRealtime21Mini = new() { Name = "gpt-realtime-2.1-mini", Version = "2026-07-07", Format = "OpenAI" };
/// <summary>
/// gpt-realtime-mini is a smaller version of gpt-realtime S2S (speech to speech) model built on chive architecture. This model excels at instruction following and is optimized for cost efficiency.
/// </summary>
[AspireValue("FoundryModels")]
public static readonly FoundryModel GptRealtimeMini = new() { Name = "gpt-realtime-mini", Version = "2025-12-15", Format = "OpenAI" };
/// <summary>
/// Gpt‑realtime‑translate is a low‑latency streaming model that converts spoken audio into translated output in real time, enabling live cross‑language communication within voice applications.
/// </summary>
[AspireValue("FoundryModels")]
public static readonly FoundryModel GptRealtimeTranslate = new() { Name = "gpt-realtime-translate", Version = "2026-05-07", Format = "OpenAI" };
/// <summary>
/// A new STT (speech to text) model with realtime capability.
/// </summary>
[AspireValue("FoundryModels")]
public static readonly FoundryModel GptRealtimeWhisper = new() { Name = "gpt-realtime-whisper", Version = "2026-05-07", Format = "OpenAI" };
/// <summary>
/// A new real-time speech-to-text (STT) model with enhanced transcription accuracy and low-latency streaming capabilities.
/// </summary>
[AspireValue("FoundryModels")]
public static readonly FoundryModel GptTranscribe = new() { Name = "gpt-transcribe", Version = "2026-07-28", Format = "OpenAI" };
/// <summary>
/// Focused on advanced reasoning and solving complex problems, including math and science tasks. Ideal for applications that require deep contextual understanding and agentic workflows.
/// </summary>
[AspireValue("FoundryModels")]
public static readonly FoundryModel O1 = new() { Name = "o1", Version = "2024-12-17", Format = "OpenAI" };
/// <summary>
/// o3 includes significant improvements on quality and safety while supporting the existing features of o1 and delivering comparable or better performance.
/// </summary>
[AspireValue("FoundryModels")]
public static readonly FoundryModel O3 = new() { Name = "o3", Version = "2025-04-16", Format = "OpenAI" };
/// <summary>
/// The o3 series of models are trained with reinforcement learning to think before they answer and perform complex reasoning. The o1-pro model uses more compute to think harder and provide consistently better answers.
/// </summary>
[AspireValue("FoundryModels")]
public static readonly FoundryModel O3DeepResearch = new() { Name = "o3-deep-research", Version = "2025-06-26", Format = "OpenAI" };
/// <summary>
/// o3-mini includes the o1 features with significant cost-efficiencies for scenarios requiring high performance.
/// </summary>
[AspireValue("FoundryModels")]
public static readonly FoundryModel O3Mini = new() { Name = "o3-mini", Version = "2025-01-31", Format = "OpenAI" };
/// <summary>
/// The o3 series of models are trained with reinforcement learning to think before they answer and perform complex reasoning. The o1-pro model uses more compute to think harder and provide consistently better answers.
/// </summary>
[AspireValue("FoundryModels")]
public static readonly FoundryModel O3Pro = new() { Name = "o3-pro", Version = "2025-06-10", Format = "OpenAI" };
/// <summary>
/// o4-mini includes significant improvements on quality and safety while supporting the existing features of o3-mini and delivering comparable or better performance.
/// </summary>
[AspireValue("FoundryModels")]
public static readonly FoundryModel O4Mini = new() { Name = "o4-mini", Version = "2025-04-16", Format = "OpenAI" };
/// <summary>
/// Text-embedding-3 series models are the latest and most capable embedding model from OpenAI.
/// </summary>
[AspireValue("FoundryModels")]
public static readonly FoundryModel TextEmbedding3Large = new() { Name = "text-embedding-3-large", Version = "1", Format = "OpenAI" };
/// <summary>
/// Text-embedding-3 series models are the latest and most capable embedding model from OpenAI.
/// </summary>
[AspireValue("FoundryModels")]
public static readonly FoundryModel TextEmbedding3Small = new() { Name = "text-embedding-3-small", Version = "1", Format = "OpenAI" };
/// <summary>
/// <para>
/// <b>Direct from Azure models</b>
/// </para>
/// <para>Direct from Azure models are a select portfolio curated for their market-differentiated capabilities:</para>
/// <list type="bullet">
/// <item>
/// <description>
/// <para>Secure and managed by Microsoft: Purchase and manage models directly through Azure with a single license, consistent support, and no third-party dependencies, backed by Azure's enterprise-grade infrastructure.</para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>Streamlined operations: Benefit from unified billing, governance, and seamless PTU portability across models hosted on Azure - all part of Microsoft Foundry.</para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>Future-ready flexibility: Access the latest models as they become available, and easily test, deploy, or switch between them within Microsoft Foundry; reducing integration effort.</para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>Cost control and optimization: Scale on demand with pay-as-you-go flexibility or reserve PTUs for predictable performance and savings.</para>
/// </description>
/// </item>
/// </list>
/// <para>Learn more about <see href="https://aka.ms/DirectfromAzure">Direct from Azure models</see>.</para>
/// <para>
/// <b>Key capabilities</b>
/// </para>
/// <para>
/// <b>About this model</b>
/// </para>
/// <para>text-embedding-ada-002 outperforms all the earlier embedding models on text search, code search, and sentence similarity tasks and gets comparable performance on text classification.</para>
/// <para>
/// <b>Key model capabilities</b>
/// </para>
/// <list type="bullet">
/// <item>
/// <description>
/// <para>Text search</para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>Code search</para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>Sentence similarity tasks</para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>Text classification</para>
/// </description>
/// </item>
/// </list>
/// <para>Note: this model can be deployed for inference, specifically for embeddings, but cannot be finetuned.</para>
/// <para>
/// <b>Use cases</b>
/// </para>
/// <para>See Responsible AI for additional considerations for responsible use.</para>
/// <para>
/// <b>Key use cases</b>
/// </para>
/// <para>The provider has not supplied this information.</para>
/// <para>
/// <b>Out of scope use cases</b>
/// </para>
/// <para>The provider has not supplied this information.</para>
/// <para>
/// <b>Pricing</b>
/// </para>
/// <para>Pricing is based on a number of factors, including deployment type and tokens used. <see href="https://azure.microsoft.com/en-us/pricing/details/ai-foundry-models/microsoft/?msockid=1775f99b2f8e614e1ba1eb792e496067">See pricing details here.</see></para>
/// <para>
/// <b>Technical specs</b>
/// </para>
/// <para>The provider has not supplied this information.</para>
/// <para>
/// <b>Training cut-off date</b>
/// </para>
/// <para>The provider has not supplied this information.</para>
/// <para>
/// <b>Training time</b>
/// </para>
/// <para>The provider has not supplied this information.</para>
/// <para>
/// <b>Input formats</b>
/// </para>
/// <para>The provider has not supplied this information.</para>
/// <para>
/// <b>Output formats</b>
/// </para>
/// <para>The provider has not supplied this information.</para>
/// <para>
/// <b>Supported languages</b>
/// </para>
/// <para>The provider has not supplied this information.</para>
/// <para>
/// <b>Sample JSON response</b>
/// </para>
/// <para>The provider has not supplied this information.</para>
/// <para>
/// <b>Model architecture</b>
/// </para>
/// <para>The provider has not supplied this information.</para>
/// <para>
/// <b>Long context</b>
/// </para>
/// <para>The provider has not supplied this information.</para>
/// <para>
/// <b>Optimizing model performance</b>
/// </para>
/// <para>The provider has not supplied this information.</para>
/// <para>
/// <b>Additional assets</b>
/// </para>
/// <para>The provider has not supplied this information.</para>
/// <para>
/// <b>Training disclosure</b>
/// </para>
/// <para>
/// <b>Training, testing and validation</b>
/// </para>
/// <para>The provider has not supplied this information.</para>
/// <para>
/// <b>Distribution</b>
/// </para>
/// <para>
/// <b>Distribution channels</b>
/// </para>
/// <para>The provider has not supplied this information.</para>
/// <para>
/// <b>More information</b>
/// </para>
/// <para>The provider has not supplied this information.</para>
/// </summary>
[AspireValue("FoundryModels")]
public static readonly FoundryModel TextEmbeddingAda002 = new() { Name = "text-embedding-ada-002", Version = "2", Format = "OpenAI" };
/// <summary>
/// <para>
/// <b>Direct from Azure models</b>
/// </para>
/// <para>Direct from Azure models are a select portfolio curated for their market-differentiated capabilities:</para>
/// <list type="bullet">
/// <item>
/// <description>
/// <para>Secure and managed by Microsoft: Purchase and manage models directly through Azure with a single license, consistent support, and no third-party dependencies, backed by Azure's enterprise-grade infrastructure.</para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>Streamlined operations: Benefit from unified billing, governance, and seamless PTU portability across models hosted on Azure - all part of Microsoft Foundry.</para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>Future-ready flexibility: Access the latest models as they become available, and easily test, deploy, or switch between them within Microsoft Foundry; reducing integration effort.</para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>Cost control and optimization: Scale on demand with pay-as-you-go flexibility or reserve PTUs for predictable performance and savings.</para>
/// </description>
/// </item>
/// </list>
/// <para>Learn more about <see href="https://aka.ms/DirectfromAzure">Direct from Azure models</see>.</para>
/// <para>
/// <b>Key capabilities</b>
/// </para>
/// <para>
/// <b>About this model</b>
/// </para>
/// <para>TTS is a model that converts text to natural sounding speech. TTS is optimized for realtime or interactive scenarios. For offline scenarios, TTS-HD provides higher quality. The API supports six different voices.</para>
/// <para>
/// <b>Key model capabilities</b>
/// </para>
/// <list type="bullet">
/// <item>
/// <description>
/// <para>TTS: optimized for speed.</para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>TTS-HD: optimized for quality.</para>
/// </description>
/// </item>
/// </list>
/// <para>
/// <b>Use cases</b>
/// </para>
/// <para>See Responsible AI for additional considerations for responsible use.</para>
/// <para>
/// <b>Key use cases</b>
/// </para>
/// <para>The provider has not supplied this information.</para>
/// <para>
/// <b>Out of scope use cases</b>
/// </para>
/// <para>The provider has not supplied this information.</para>
/// <para>
/// <b>Pricing</b>
/// </para>
/// <para>Pricing is based on a number of factors, including deployment type and tokens used. <see href="https://azure.microsoft.com/en-us/pricing/details/ai-foundry-models/microsoft/?msockid=1775f99b2f8e614e1ba1eb792e496067">See pricing details here.</see></para>
/// <para>
/// <b>Technical specs</b>
/// </para>
/// <para>The provider has not supplied this information.</para>
/// <para>
/// <b>Training cut-off date</b>
/// </para>
/// <para>The provider has not supplied this information.</para>
/// <para>
/// <b>Training time</b>
/// </para>
/// <para>The provider has not supplied this information.</para>
/// <para>
/// <b>Input formats</b>
/// </para>
/// <para>Max request data size: 4,096 chars can be converted from text to speech per API request.</para>
/// <para>
/// <b>Output formats</b>
/// </para>
/// <para>The provider has not supplied this information.</para>
/// <para>
/// <b>Supported languages</b>
/// </para>
/// <para>The provider has not supplied this information.</para>
/// <para>
/// <b>Sample JSON response</b>
/// </para>
/// <para>The provider has not supplied this information.</para>
/// <para>
/// <b>Model architecture</b>
/// </para>
/// <para>The provider has not supplied this information.</para>
/// <para>
/// <b>Long context</b>
/// </para>
/// <para>The provider has not supplied this information.</para>
/// <para>
/// <b>Optimizing model performance</b>
/// </para>
/// <para>The provider has not supplied this information.</para>
/// <para>
/// <b>Additional assets</b>
/// </para>
/// <para>The provider has not supplied this information.</para>
/// <para>
/// <b>Training disclosure</b>
/// </para>
/// <para>
/// <b>Training, testing and validation</b>
/// </para>
/// <para>The provider has not supplied this information.</para>
/// <para>
/// <b>Distribution</b>
/// </para>
/// <para>
/// <b>Distribution channels</b>
/// </para>
/// <para>The provider has not supplied this information.</para>
/// <para>
/// <b>More information</b>
/// </para>
/// <para>The provider has not supplied this information.</para>
/// </summary>
[AspireValue("FoundryModels")]
public static readonly FoundryModel Tts = new() { Name = "tts", Version = "001", Format = "OpenAI" };
/// <summary>
/// <para>
/// <b>Direct from Azure models</b>
/// </para>
/// <para>Direct from Azure models are a select portfolio curated for their market-differentiated capabilities:</para>
/// <list type="bullet">
/// <item>
/// <description>
/// <para>Secure and managed by Microsoft: Purchase and manage models directly through Azure with a single license, consistent support, and no third-party dependencies, backed by Azure's enterprise-grade infrastructure.</para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>Streamlined operations: Benefit from unified billing, governance, and seamless PTU portability across models hosted on Azure - all part of Microsoft Foundry.</para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>Future-ready flexibility: Access the latest models as they become available, and easily test, deploy, or switch between them within Microsoft Foundry; reducing integration effort.</para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>Cost control and optimization: Scale on demand with pay-as-you-go flexibility or reserve PTUs for predictable performance and savings.</para>
/// </description>
/// </item>
/// </list>
/// <para>Learn more about <see href="https://aka.ms/DirectfromAzure">Direct from Azure models</see>.</para>
/// <para>
/// <b>Key capabilities</b>
/// </para>
/// <para>
/// <b>About this model</b>
/// </para>
/// <para>TTS-HD is a model that converts text to natural sounding speech.</para>
/// <para>
/// <b>Key model capabilities</b>
/// </para>
/// <list type="bullet">
/// <item>
/// <description>
/// <para>TTS: optimized for speed.</para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>TTS-HD: optimized for quality.</para>
/// </description>
/// </item>
/// </list>
/// <para>
/// <b>Use cases</b>
/// </para>
/// <para>See Responsible AI for additional considerations for responsible use.</para>
/// <para>
/// <b>Key use cases</b>
/// </para>
/// <para>TTS is optimized for realtime or interactive scenarios. For offline scenarios, TTS-HD provides higher quality.</para>
/// <para>
/// <b>Out of scope use cases</b>
/// </para>
/// <para>The provider has not supplied this information.</para>
/// <para>
/// <b>Pricing</b>
/// </para>
/// <para>Pricing is based on a number of factors, including deployment type and tokens used. <see href="https://azure.microsoft.com/en-us/pricing/details/ai-foundry-models/microsoft/?msockid=1775f99b2f8e614e1ba1eb792e496067">See pricing details here.</see></para>
/// <para>
/// <b>Technical specs</b>
/// </para>
/// <para>The provider has not supplied this information.</para>
/// <para>
/// <b>Training cut-off date</b>
/// </para>
/// <para>The provider has not supplied this information.</para>
/// <para>
/// <b>Training time</b>
/// </para>
/// <para>The provider has not supplied this information.</para>
/// <para>
/// <b>Input formats</b>
/// </para>
/// <para>Max request data size: 4,096 chars can be converted from text to speech per API request.</para>
/// <para>
/// <b>Output formats</b>
/// </para>
/// <para>The provider has not supplied this information.</para>
/// <para>
/// <b>Supported languages</b>
/// </para>
/// <para>The provider has not supplied this information.</para>
/// <para>
/// <b>Sample JSON response</b>
/// </para>
/// <para>The provider has not supplied this information.</para>
/// <para>
/// <b>Model architecture</b>
/// </para>
/// <para>The provider has not supplied this information.</para>
/// <para>
/// <b>Long context</b>
/// </para>
/// <para>The provider has not supplied this information.</para>
/// <para>
/// <b>Optimizing model performance</b>
/// </para>
/// <para>The provider has not supplied this information.</para>
/// <para>
/// <b>Additional assets</b>
/// </para>
/// <para>The provider has not supplied this information.</para>
/// <para>
/// <b>Training disclosure</b>
/// </para>
/// <para>
/// <b>Training, testing and validation</b>
/// </para>
/// <para>The provider has not supplied this information.</para>
/// <para>
/// <b>Distribution</b>
/// </para>
/// <para>
/// <b>Distribution channels</b>
/// </para>
/// <para>The provider has not supplied this information.</para>
/// <para>
/// <b>More information</b>
/// </para>
/// <para>The provider has not supplied this information.</para>
/// </summary>
[AspireValue("FoundryModels")]
public static readonly FoundryModel TtsHd = new() { Name = "tts-hd", Version = "001", Format = "OpenAI" };
/// <summary>
/// <para>
/// <b>Direct from Azure models</b>
/// </para>
/// <para>Direct from Azure models are a select portfolio curated for their market-differentiated capabilities:</para>
/// <list type="bullet">
/// <item>
/// <description>
/// <para>Secure and managed by Microsoft: Purchase and manage models directly through Azure with a single license, consistent support, and no third-party dependencies, backed by Azure's enterprise-grade infrastructure.</para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>Streamlined operations: Benefit from unified billing, governance, and seamless PTU portability across models hosted on Azure - all part of Microsoft Foundry.</para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>Future-ready flexibility: Access the latest models as they become available, and easily test, deploy, or switch between them within Microsoft Foundry; reducing integration effort.</para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>Cost control and optimization: Scale on demand with pay-as-you-go flexibility or reserve PTUs for predictable performance and savings.</para>
/// </description>
/// </item>
/// </list>
/// <para>Learn more about <see href="https://aka.ms/DirectfromAzure">Direct from Azure models</see>.</para>
/// <para>
/// <b>Key capabilities</b>
/// </para>
/// <para>
/// <b>About this model</b>
/// </para>
/// <para>The Whisper models are trained for speech recognition and translation tasks, capable of transcribing speech audio into the text in the language it is spoken (automatic speech recognition) as well as translated into English (speech translation).</para>
/// <para>
/// <b>Key model capabilities</b>
/// </para>
/// <list type="bullet">
/// <item>
/// <description>
/// <para>Speech recognition (automatic speech recognition)</para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>Speech translation into English</para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>Processing of audio up to 25mb per API request</para>
/// </description>
/// </item>
/// </list>
/// <para>
/// <b>Use cases</b>
/// </para>
/// <para>See Responsible AI for additional considerations for responsible use.</para>
/// <para>
/// <b>Key use cases</b>
/// </para>
/// <para>The provider has not supplied this information.</para>
/// <para>
/// <b>Out of scope use cases</b>
/// </para>
/// <para>The provider has not supplied this information.</para>
/// <para>
/// <b>Pricing</b>
/// </para>
/// <para>Pricing is based on a number of factors, including deployment type and tokens used. <see href="https://azure.microsoft.com/en-us/pricing/details/ai-foundry-models/microsoft/?msockid=1775f99b2f8e614e1ba1eb792e496067">See pricing details here.</see></para>
/// <para>
/// <b>Technical specs</b>
/// </para>
/// <para>The provider has not supplied this information.</para>
/// <para>
/// <b>Training cut-off date</b>
/// </para>
/// <para>The provider has not supplied this information.</para>
/// <para>
/// <b>Training time</b>
/// </para>
/// <para>The provider has not supplied this information.</para>
/// <para>
/// <b>Input formats</b>
/// </para>
/// <para>Max request data size: 25mb of audio can be converted from speech to text per API request.</para>
/// <para>
/// <b>Output formats</b>
/// </para>
/// <para>The provider has not supplied this information.</para>
/// <para>
/// <b>Supported languages</b>
/// </para>
/// <para>The provider has not supplied this information.</para>
/// <para>
/// <b>Sample JSON response</b>
/// </para>
/// <para>The provider has not supplied this information.</para>
/// <para>
/// <b>Model architecture</b>
/// </para>
/// <para>The provider has not supplied this information.</para>
/// <para>
/// <b>Long context</b>
/// </para>
/// <para>The provider has not supplied this information.</para>
/// <para>
/// <b>Optimizing model performance</b>
/// </para>
/// <para>The provider has not supplied this information.</para>
/// <para>
/// <b>Additional assets</b>
/// </para>
/// <para>The provider has not supplied this information.</para>
/// <para>
/// <b>Training disclosure</b>
/// </para>
/// <para>
/// <b>Training, testing and validation</b>
/// </para>
/// <para>Researchers at OpenAI developed the models to study the robustness of speech processing systems trained under large-scale weak supervision.</para>
/// <para>
/// <b>Distribution</b>
/// </para>
/// <para>
/// <b>Distribution channels</b>
/// </para>
/// <para>The provider has not supplied this information.</para>
/// <para>
/// <b>More information</b>
/// </para>
/// <para>The provider has not supplied this information.</para>
/// </summary>
[AspireValue("FoundryModels")]
public static readonly FoundryModel Whisper = new() { Name = "whisper", Version = "001", Format = "OpenAI" };
}
/// <summary>
/// Models published by StabilityAI.
/// </summary>
public static partial class StabilityAI
{
/// <summary>
/// <para>
/// <b>Models from Microsoft, Partners, and Community</b>
/// </para>
/// <para>Models from Microsoft, Partners, and Community models are a select portfolio of curated models both general-purpose and niche models across diverse scenarios by developed by Microsoft teams, partners, and community contributors</para>
/// <list type="bullet">
/// <item>
/// <description>
/// <para>
/// <b>Managed by Microsoft:</b> Purchase and manage models directly through Azure with a single license, world class support and enterprise grade Azure infrastructure</para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>
/// <b>Validated by providers:</b> Each model is validated and maintained by its respective provider, with Azure offering integration and deployment guidance.</para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>
/// <b>Innovation and agility:</b> Combines Microsoft research models with rapid, community-driven advancements.</para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>
/// <b>Seamless Azure integration:</b> Standard Microsoft Foundry experience, with support managed by the model provider.</para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>
/// <b>Flexible deployment:</b> Deployable as <b>Managed Compute</b> or <b>Serverless API</b>, based on provider preference.</para>
/// </description>
/// </item>
/// </list>
/// <para>
/// <see href="https://aka.ms/Azure1P3PModels">Learn more about models from Microsoft, Partners, and Community</see>
/// </para>
/// <para>
/// <b>Key capabilities</b>
/// </para>
/// <para>
/// <b>About this model</b>
/// </para>
/// <para>Stable Diffusion 3.5 Large produces diverse outputs, creating images that are representative of the world, with different skin tones and features, all without requiring extensive prompting.</para>
/// <para>It also offers unmatched versatility, generating visuals in virtually any style, from 3D and photography to painting and line art. Our analysis shows that Stable Diffusion 3.5 Large leads the market in prompt adherence and rivals significantly larger models in image quality.</para>
/// <para>
/// <b>Key model capabilities</b>
/// </para>
/// <para>Stable Diffusion 3.5 Large produces diverse outputs, creating images that are representative of the world, with different skin tones and features, all without requiring extensive prompting.</para>
/// <para>It also offers unmatched versatility, generating visuals in virtually any style, from 3D and photography to painting and line art. Our analysis shows that Stable Diffusion 3.5 Large leads the market in prompt adherence and rivals significantly larger models in image quality.</para>
/// <para>
/// <b>Use cases</b>
/// </para>
/// <para>See Responsible AI for additional considerations for responsible use.</para>
/// <para>
/// <b>Key use cases</b>
/// </para>
/// <para>Advertising and marketing Media and entertainment, Gaming and metaverse Education and training Retail Publishing</para>
/// <para>
/// <b>Out of scope use cases</b>
/// </para>
/// <para>The model was not trained to be factual or true representations of people or events. As such, using the model to generate such content is out-of-scope of the abilities of this model.</para>
/// <para>
/// <b>Pricing</b>
/// </para>
/// <para>Pricing is based on a number of factors, including deployment type and tokens used. <see href="https://azure.microsoft.com/en-us/pricing/details/ai-foundry-models/microsoft/?msockid=1775f99b2f8e614e1ba1eb792e496067">See pricing details here.</see></para>
/// <para>
/// <b>Technical specs</b>
/// </para>
/// <para>At 8.1 billion parameters, with superior quality and prompt adherence, this base model is the most powerful in the Stable Diffusion family. This model is ideal for professional use cases at 1 megapixel resolution.</para>
/// <para>
/// <b>Training cut-off date</b>
/// </para>
/// <para>The provider has not supplied this information.</para>
/// <para>
/// <b>Training time</b>
/// </para>
/// <para>The provider has not supplied this information.</para>
/// <para>
/// <b>Input formats</b>
/// </para>
/// <para>The provider has not supplied this information.</para>
/// <para>
/// <b>Output formats</b>
/// </para>
/// <para>The provider has not supplied this information.</para>
/// <para>
/// <b>Supported languages</b>
/// </para>
/// <para>The provider has not supplied this information.</para>
/// <para>
/// <b>Sample JSON response</b>
/// </para>
/// <para>The provider has not supplied this information.</para>
/// <para>
/// <b>Model architecture</b>
/// </para>
/// <para>The provider has not supplied this information.</para>
/// <para>
/// <b>Long context</b>
/// </para>
/// <para>The provider has not supplied this information.</para>
/// <para>
/// <b>Optimizing model performance</b>
/// </para>
/// <para>The provider has not supplied this information.</para>
/// <para>
/// <b>Additional assets</b>
/// </para>
/// <para>The provider has not supplied this information.</para>
/// <para>
/// <b>Training disclosure</b>
/// </para>
/// <para>
/// <b>Training, testing and validation</b>
/// </para>
/// <para>This model was trained on a wide variety of data, including synthetic data and filtered publicly available data.</para>
/// <para>
/// <b>Distribution</b>
/// </para>
/// <para>
/// <b>Distribution channels</b>
/// </para>
/// <para>The provider has not supplied this information.</para>
/// <para>
/// <b>More information</b>
/// </para>
/// <para>We believe in safe, responsible AI practices and take deliberate measures to ensure Integrity starts at the early stages of development. This means we have taken and continue to take reasonable steps to prevent the misuse of Stable Diffusion 3.5 by bad actors. For more information about our approach to Safety please visit our Stable Safety page.</para>
/// </summary>
[AspireValue("FoundryModels")]
public static readonly FoundryModel StableDiffusion35Large = new() { Name = "Stable-Diffusion-3.5-Large", Version = "1", Format = "StabilityAI" };
/// <summary>
/// <para>
/// <b>Models from Microsoft, Partners, and Community</b>
/// </para>
/// <para>Models from Microsoft, Partners, and Community models are a select portfolio of curated models both general-purpose and niche models across diverse scenarios by developed by Microsoft teams, partners, and community contributors</para>
/// <list type="bullet">
/// <item>
/// <description>
/// <para>
/// <b>Managed by Microsoft:</b> Purchase and manage models directly through Azure with a single license, world class support and enterprise grade Azure infrastructure</para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>
/// <b>Validated by providers:</b> Each model is validated and maintained by its respective provider, with Azure offering integration and deployment guidance.</para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>
/// <b>Innovation and agility:</b> Combines Microsoft research models with rapid, community-driven advancements.</para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>
/// <b>Seamless Azure integration:</b> Standard Microsoft Foundry experience, with support managed by the model provider.</para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>
/// <b>Flexible deployment:</b> Deployable as <b>Managed Compute</b> or <b>Serverless API</b>, based on provider preference.</para>
/// </description>
/// </item>
/// </list>
/// <para>
/// <see href="https://aka.ms/Azure1P3PModels">Learn more about models from Microsoft, Partners, and Community</see>
/// </para>
/// <para>
/// <b>Key capabilities</b>
/// </para>
/// <para>
/// <b>About this model</b>
/// </para>
/// <para>Leveraging an enhanced version of SDXL, Stable Image Core, delivers exceptional speed and efficiency while maintaining the high-quality output synonymous with Stable Diffusion models.</para>
/// <para>
/// <b>Key model capabilities</b>
/// </para>
/// <para>The provider has not supplied this information.</para>
/// <para>
/// <b>Use cases</b>
/// </para>
/// <para>See Responsible AI for additional considerations for responsible use.</para>
/// <para>
/// <b>Key use cases</b>
/// </para>
/// <list type="number">
/// <item>
/// <description>
/// <para>Advertising and marketing</para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>Media and entertainment</para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>Gaming and metaverse</para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>Education and training</para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>Retail</para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>Publishing</para>
/// </description>
/// </item>
/// </list>
/// <para>
/// <b>Out of scope use cases</b>
/// </para>
/// <para>The provider has not supplied this information.</para>
/// <para>
/// <b>Pricing</b>
/// </para>
/// <para>Pricing is based on a number of factors, including deployment type and tokens used. <see href="https://azure.microsoft.com/en-us/pricing/details/ai-foundry-models/microsoft/?msockid=1775f99b2f8e614e1ba1eb792e496067">See pricing details here.</see></para>
/// <para>
/// <b>Technical specs</b>
/// </para>
/// <para>The provider has not supplied this information.</para>
/// <para>
/// <b>Training cut-off date</b>
/// </para>
/// <para>The provider has not supplied this information.</para>
/// <para>
/// <b>Training time</b>
/// </para>
/// <para>The provider has not supplied this information.</para>
/// <para>
/// <b>Input formats</b>
/// </para>
/// <para>The provider has not supplied this information.</para>
/// <para>
/// <b>Output formats</b>
/// </para>
/// <para>The provider has not supplied this information.</para>
/// <para>
/// <b>Supported languages</b>
/// </para>
/// <para>The provider has not supplied this information.</para>
/// <para>
/// <b>Sample JSON response</b>
/// </para>
/// <para>The provider has not supplied this information.</para>
/// <para>
/// <b>Model architecture</b>
/// </para>
/// <para>The provider has not supplied this information.</para>
/// <para>
/// <b>Long context</b>
/// </para>
/// <para>The provider has not supplied this information.</para>
/// <para>
/// <b>Optimizing model performance</b>
/// </para>
/// <para>The provider has not supplied this information.</para>
/// <para>
/// <b>Additional assets</b>
/// </para>
/// <para>The provider has not supplied this information.</para>
/// <para>
/// <b>Training disclosure</b>
/// </para>
/// <para>
/// <b>Training, testing and validation</b>
/// </para>
/// <para>The provider has not supplied this information.</para>
/// <para>
/// <b>Distribution</b>
/// </para>
/// <para>
/// <b>Distribution channels</b>
/// </para>
/// <para>The provider has not supplied this information.</para>
/// <para>
/// <b>More information</b>
/// </para>
/// <para>We believe in safe, responsible AI practices and take deliberate measures to ensure Integrity starts at the early stages of development. For more information about our approach to Safety please visit our <see href="https://stability.ai/safety">Stable Safety</see> page.</para>
/// </summary>
[AspireValue("FoundryModels")]
public static readonly FoundryModel StableImageCore = new() { Name = "Stable-Image-Core", Version = "1", Format = "StabilityAI" };
/// <summary>
/// <para>
/// <b>Models from Microsoft, Partners, and Community</b>
/// </para>
/// <para>Models from Microsoft, Partners, and Community models are a select portfolio of curated models both general-purpose and niche models across diverse scenarios by developed by Microsoft teams, partners, and community contributors</para>
/// <list type="bullet">
/// <item>
/// <description>
/// <para>
/// <b>Managed by Microsoft:</b> Purchase and manage models directly through Azure with a single license, world class support and enterprise grade Azure infrastructure</para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>
/// <b>Validated by providers:</b> Each model is validated and maintained by its respective provider, with Azure offering integration and deployment guidance.</para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>
/// <b>Innovation and agility:</b> Combines Microsoft research models with rapid, community-driven advancements.</para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>
/// <b>Seamless Azure integration:</b> Standard Microsoft Foundry experience, with support managed by the model provider.</para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>
/// <b>Flexible deployment:</b> Deployable as <b>Managed Compute</b> or <b>Serverless API</b>, based on provider preference.</para>
/// </description>
/// </item>
/// </list>
/// <para>
/// <see href="https://aka.ms/Azure1P3PModels">Learn more about models from Microsoft, Partners, and Community</see>
/// </para>
/// <para>
/// <b>Key capabilities</b>
/// </para>
/// <para>
/// <b>About this model</b>
/// </para>
/// <para>Powered by the advanced capabilities of Stable Diffusion 3.5 Large, Stable Image Ultra sets a new standard in photorealism. It also excels in typography, dynamic lighting, and vibrant color rendering.</para>
/// <para>
/// <b>Key model capabilities</b>
/// </para>
/// <list type="bullet">
/// <item>
/// <description>
/// <para>Typography</para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>Dynamic lighting</para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>Vibrant color rendering</para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>Product imagery for marketing and advertising</para>
/// </description>
/// </item>
/// </list>
/// <para>
/// <b>Use cases</b>
/// </para>
/// <para>See Responsible AI for additional considerations for responsible use.</para>
/// <para>
/// <b>Key use cases</b>
/// </para>
/// <list type="number">
/// <item>
/// <description>
/// <para>Advertising and marketing</para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>Media and entertainment</para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>Gaming and metaverse</para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>Education and training</para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>Retail</para>
/// </description>
/// </item>
/// <item>
/// <description>
/// <para>Publishing</para>
/// </description>
/// </item>
/// </list>
/// <para>
/// <b>Out of scope use cases</b>
/// </para>
/// <para>The provider has not supplied this information.</para>
/// <para>
/// <b>Pricing</b>
/// </para>
/// <para>Pricing is based on a number of factors, including deployment type and tokens used. <see href="https://azure.microsoft.com/en-us/pricing/details/ai-foundry-models/microsoft/?msockid=1775f99b2f8e614e1ba1eb792e496067">See pricing details here.</see></para>
/// <para>
/// <b>Technical specs</b>
/// </para>
/// <para>The provider has not supplied this information.</para>
/// <para>
/// <b>Training cut-off date</b>
/// </para>
/// <para>The provider has not supplied this information.</para>
/// <para>
/// <b>Training time</b>
/// </para>
/// <para>The provider has not supplied this information.</para>
/// <para>
/// <b>Input formats</b>
/// </para>
/// <para>The provider has not supplied this information.</para>
/// <para>
/// <b>Output formats</b>
/// </para>
/// <para>The provider has not supplied this information.</para>
/// <para>
/// <b>Supported languages</b>
/// </para>
/// <para>The provider has not supplied this information.</para>
/// <para>
/// <b>Sample JSON response</b>
/// </para>
/// <para>The provider has not supplied this information.</para>
/// <para>
/// <b>Model architecture</b>
/// </para>
/// <para>The provider has not supplied this information.</para>
/// <para>
/// <b>Long context</b>
/// </para>
/// <para>The provider has not supplied this information.</para>
/// <para>
/// <b>Optimizing model performance</b>
/// </para>
/// <para>The provider has not supplied this information.</para>
/// <para>
/// <b>Additional assets</b>
/// </para>
/// <para>The provider has not supplied this information.</para>
/// <para>
/// <b>Training disclosure</b>
/// </para>
/// <para>
/// <b>Training, testing and validation</b>
/// </para>
/// <para>The provider has not supplied this information.</para>
/// <para>
/// <b>Distribution</b>
/// </para>
/// <para>
/// <b>Distribution channels</b>
/// </para>
/// <para>The provider has not supplied this information.</para>
/// <para>
/// <b>More information</b>
/// </para>
/// <para>We believe in safe, responsible AI practices and take deliberate measures to ensure Integrity starts at the early stages of development. For more information about our approach to Safety please visit our <see href="https://stability.ai/safety">Stable Safety</see> page.</para>
/// </summary>
[AspireValue("FoundryModels")]
public static readonly FoundryModel StableImageUltra = new() { Name = "Stable-Image-Ultra", Version = "1", Format = "StabilityAI" };
}
/// <summary>
/// Models published by xAI.
/// </summary>
public static partial class XAI
{
/// <summary>
/// Grok 4 is the latest reasoning model from xAI with advanced reasoning and tool-use capabilities, enabling it to achieve new state-of-the-art performance across challenging academic and industry benchmarks.
/// </summary>
[AspireValue("FoundryModels")]
public static readonly FoundryModel Grok4 = new() { Name = "grok-4", Version = "1", Format = "xAI" };
/// <summary>
/// Grok 4.1 Fast Non‑Reasoning is designed for low‑latency, near‑instant responses, emphasizing speed, high‑quality outputs, and smooth tool‑calling in agentic workflows, making it well‑suited for high‑throughput, real‑time scenarios where immediate responses
/// </summary>
[AspireValue("FoundryModels")]
public static readonly FoundryModel Grok41FastNonReasoning = new() { Name = "grok-4-1-fast-non-reasoning", Version = "1", Format = "xAI" };
/// <summary>
/// Grok 4.1 Fast Reasoning is a frontier multimodal model built for high‑performance, agentic execution—combining strong reasoning, advanced tool calling, and agentic search to handle complex tasks with speed and precision. It delivers natural, fluid dialogue
/// </summary>
[AspireValue("FoundryModels")]
public static readonly FoundryModel Grok41FastReasoning = new() { Name = "grok-4-1-fast-reasoning", Version = "1", Format = "xAI" };
/// <summary>
/// Grok 4.2 is xAI’s latest large language model, built for strong reasoning, multimodal understanding, and enterprise use. It improves instruction following, honesty, and calibration over earlier Grok versions, while supporting both single‑agent and multi‑ag
/// </summary>
[AspireValue("FoundryModels")]
public static readonly FoundryModel Grok420NonReasoning = new() { Name = "grok-4-20-non-reasoning", Version = "1", Format = "xAI" };
/// <summary>
/// Grok 4.2 is xAI’s latest large language model, built for strong reasoning, multimodal understanding, and enterprise use. It improves instruction following, honesty, and calibration over earlier Grok versions, while supporting both single‑agent and multi‑ag
/// </summary>
[AspireValue("FoundryModels")]
public static readonly FoundryModel Grok420Reasoning = new() { Name = "grok-4-20-reasoning", Version = "1", Format = "xAI" };
/// <summary>
/// Grok 4.3 is the latest model from xAI, with advanced reasoning, productivity, and multi-agent capabilities, enabling it to achieve state-of-the-art performance across challenging academic and industry benchmarks.
/// </summary>
[AspireValue("FoundryModels")]
public static readonly FoundryModel Grok43 = new() { Name = "grok-4.3", Version = "1", Format = "xAI" };
/// <summary>
/// Grok Code Fast 1 is a fast, economical AI model for agentic coding, built from scratch with a new architecture, trained on programming-rich data, and fine-tuned for real-world coding tasks like bug fixes and project setup.
/// </summary>
[AspireValue("FoundryModels")]
public static readonly FoundryModel GrokCodeFast1 = new() { Name = "grok-code-fast-1", Version = "1", Format = "xAI" };
}
}