using static AIStudio.Provider.Capability;
using static AIStudio.Provider.LLMProviders;
namespace AIStudio.Tests.Models.Corpus;
///
/// The answers the rebuild has to change, one entry per model.
///
///
/// Every entry here was found by running the corpus against the rules as they stand and reading
/// what came back. They are kept out of the snapshot so that the rebuild does not copy them: a
/// snapshot says "do not change this", and a wrong answer is the one thing that must change.
///
/// Three kinds of mistake are collected below, and they are the three the new architecture is meant
/// to make impossible rather than fix one by one:
///
/// - A model which is not a chat model at all is answered as if it were one. The app already knows
/// better: it asks its providers for embedding and transcription models through methods of their
/// own. The capability rules never hear about that and hand out tool calling and image input.
/// - The same model gets two different answers depending on which spelling it arrives in. That is
/// the routing graph leaking into the rules, and it is what the explicit hosts are for.
/// - A prefix rule swallows a variant whose name says the opposite. That is priority written by
/// hand, and it is what computed specificity is for.
///
public static class ExpectedChanges
{
///
/// Where the app itself states that a model is not a chat model.
///
private const string THE_APP_LISTS_IT_AS_AN_EMBEDDING_MODEL = "The app asks every provider for its embedding models separately, through IProvider.GetEmbeddingModels.";
///
/// Every model whose answer has to change.
///
public static readonly IReadOnlyList ENTRIES =
[
//
// Embedding models. They turn text into a vector; there is nothing for them to call a
// function with and no image for them to look at. What they need stated is that they embed,
// which the capability vocabulary has a word for and the rules never use.
//
new(OPEN_AI, "text-embedding-3-large",
AnswerToday: [TEXT_INPUT, MULTIPLE_IMAGE_INPUT, TEXT_OUTPUT, FUNCTION_CALLING, RESPONSES_API, WEB_SEARCH],
AnswerWanted: [TEXT_INPUT, EMBEDDING],
Reason: "An embedding model is answered with the OpenAI chat default, tool calling and image input included.",
Source: THE_APP_LISTS_IT_AS_AN_EMBEDDING_MODEL),
new(GOOGLE, "text-embedding-004",
AnswerToday: [TEXT_INPUT, MULTIPLE_IMAGE_INPUT, TEXT_OUTPUT, FUNCTION_CALLING, CHAT_COMPLETION_API],
AnswerWanted: [TEXT_INPUT, EMBEDDING],
Reason: "An embedding model is answered with the Google default for everything which is not a Gemini.",
Source: THE_APP_LISTS_IT_AS_AN_EMBEDDING_MODEL),
new(ALIBABA_CLOUD, "text-embedding-v3",
AnswerToday: [TEXT_INPUT, TEXT_OUTPUT, FUNCTION_CALLING, CHAT_COMPLETION_API],
AnswerWanted: [TEXT_INPUT, EMBEDDING],
Reason: "An embedding model is answered with the Alibaba default, because its name starts with none of the Qwen prefixes.",
Source: "Provider/AlibabaCloud/ProviderAlibabaCloud.cs adds it in GetEmbeddingModels and filters the catalog by the prefix \"text-embedding-\"."),
new(SELF_HOSTED, "nomic-embed-text:latest",
AnswerToday: [TEXT_INPUT, TEXT_OUTPUT, FUNCTION_CALLING, CHAT_COMPLETION_API],
AnswerWanted: [TEXT_INPUT, EMBEDDING],
Reason: "An embedding model reaches the global fallback, which assumes an instruction-tuned model that calls functions.",
Source: THE_APP_LISTS_IT_AS_AN_EMBEDDING_MODEL),
new(SELF_HOSTED, "granite-embedding:278m",
AnswerToday: [TEXT_INPUT, TEXT_OUTPUT, FUNCTION_CALLING, CHAT_COMPLETION_API],
AnswerWanted: [TEXT_INPUT, EMBEDDING],
Reason: "The Granite block answers about a checkpoint which embeds, and it hands out tool calling for it.",
Source: THE_APP_LISTS_IT_AS_AN_EMBEDDING_MODEL),
new(GWDG, "e5-mistral-7b-instruct",
AnswerToday: [TEXT_INPUT, TEXT_OUTPUT, FUNCTION_CALLING, CHAT_COMPLETION_API],
AnswerWanted: [TEXT_INPUT, EMBEDDING],
Reason: "An embedding model is judged by the Mistral rules, because its name carries the word.",
Source: THE_APP_LISTS_IT_AS_AN_EMBEDDING_MODEL),
//
// Transcription models. They take speech and write it down. Three of the four are in the
// app's own list of transcription models, with the provider's documentation next to them.
//
new(OPEN_AI, "whisper-1",
AnswerToday: [TEXT_INPUT, MULTIPLE_IMAGE_INPUT, TEXT_OUTPUT, FUNCTION_CALLING, RESPONSES_API, WEB_SEARCH],
AnswerWanted: [SPEECH_INPUT, TEXT_OUTPUT],
Reason: "A transcription model is answered with the OpenAI chat default, web search and image input included.",
Source: "The app asks every provider for its transcription models separately, through IProvider.GetTranscriptionModels."),
new(FIREWORKS, "whisper-v3",
AnswerToday: [TEXT_INPUT, TEXT_OUTPUT, FUNCTION_CALLING, CHAT_COMPLETION_API],
AnswerWanted: [SPEECH_INPUT, TEXT_OUTPUT],
Reason: "A transcription model reaches the global fallback and is told it calls functions.",
Source: "Provider/Fireworks/ProviderFireworks.cs returns it from GetTranscriptionModels."),
new(GWDG, "whisper-large-v2",
AnswerToday: [TEXT_INPUT, TEXT_OUTPUT, FUNCTION_CALLING, CHAT_COMPLETION_API],
AnswerWanted: [SPEECH_INPUT, TEXT_OUTPUT],
Reason: "A transcription model reaches the global fallback and is told it calls functions.",
Source: "Provider/GWDG/ProviderGWDG.cs returns it from GetTranscriptionModels."),
new(GROQ, "whisper-large-v3-turbo",
AnswerToday: [TEXT_INPUT, TEXT_OUTPUT, FUNCTION_CALLING, CHAT_COMPLETION_API],
AnswerWanted: [SPEECH_INPUT, TEXT_OUTPUT],
Reason: "A transcription model reaches the global fallback and is told it calls functions.",
Source: "Same model family as the Whisper entries the app lists for Fireworks and GWDG."),
//
// One model, two spellings, two answers.
//
new(LITE_LLM, "bedrock/anthropic.claude-3-5-sonnet-20241022-v2:0",
AnswerToday: [TEXT_INPUT, TEXT_OUTPUT, FUNCTION_CALLING, CHAT_COMPLETION_API],
AnswerWanted: [TEXT_INPUT, MULTIPLE_IMAGE_INPUT, TEXT_OUTPUT, FUNCTION_CALLING, CHAT_COMPLETION_API],
Reason: "Claude 3.5 Sonnet loses its image input when it arrives under the Bedrock spelling: the vendor sits behind a dot rather than a slash, so neither the gateway detection nor the reseller check finds it.",
Source: "The same model as \"anthropic/claude-sonnet-4-0\" and the other Claude entries of this corpus, which all report image input."),
new(HELMHOLTZ, "01 - GPT-5.5 - great overall performance",
AnswerToday: [TEXT_INPUT, MULTIPLE_IMAGE_INPUT, TEXT_OUTPUT, FUNCTION_CALLING, WEB_SEARCH, CHAT_COMPLETION_API],
AnswerWanted: [TEXT_INPUT, MULTIPLE_IMAGE_INPUT, TEXT_OUTPUT, FUNCTION_CALLING, REASONING_BY_DEFAULT, WEB_SEARCH, CHAT_COMPLETION_API],
Reason: "The descriptive name is recognized as a GPT model and then placed nowhere: every version rule matches the beginning of the name, which here is the list number. The model loses the reasoning it is known for.",
Source: "The GWDG entry \"gpt-5.5\" of this corpus is the same model and does report reasoning by default."),
//
// A prefix rule swallowing the variant which says the opposite.
//
new(OPEN_AI, "gpt-5-chat-latest",
AnswerToday: [TEXT_INPUT, MULTIPLE_IMAGE_INPUT, TEXT_OUTPUT, FUNCTION_CALLING, ALWAYS_REASONING, WEB_SEARCH, RESPONSES_API],
AnswerWanted: [TEXT_INPUT, MULTIPLE_IMAGE_INPUT, TEXT_OUTPUT, FUNCTION_CALLING, WEB_SEARCH, RESPONSES_API],
Reason: "The alias for the non-reasoning GPT-5 is claimed by the \"gpt-5-\" prefix rule and is told it always reasons, which is the one thing its name rules out.",
Source: "OpenAI names this alias as the non-reasoning model of the GPT-5 line; the corpus entry \"gpt-5\" next to it is the reasoning one."),
];
}