feat: Add support for 1M token limit in conversation history calculations and update model options

[AshAnand34]

Resolves Issue #826 (1M token support for claude sonnet)

[vercel]

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[phy101]

I don't think it will work as you propose it.

there is no model "claude-sonnet-4-1m"
you need to add in the "claude-sonnet-4"

"anthropic-beta": "context-1m-2025-08-07",

[phy101]

You also need to update the costs according.

Prompts ≤ 200K | $3 / MTok | $15 / MTok
Prompts > 200K | $6 / MTok | $22.50 / MTok

[andrewpsp]

#833 specifically creating the new model to do a function lookup instead of reliance on the static implementation

// Canonical metadata for all supported models

export type ModelFamily = "Anthropic Claude" | "OpenAI GPT" | "Google Gemini" | "DeepSeek" | "Qwen" | "Meta Llama" | "Grok" | "Other";

export interface ModelMetadata {
 label: string;
 modelName: string;
 modelFamily: ModelFamily;
 maxInternalTokens: number | undefined;
 contextWindow: number;
 notableFeatures?: string[];
 costPerMillionTokens?: {
   input: number;
   output: number;
 };
}

export const MODEL_METADATA: Record<string, ModelMetadata> = {
 "anthropic:claude-sonnet-4-1m": {
   label: "Claude Sonnet 4 (1M Context)",
   modelName: "anthropic:claude-sonnet-4-1m",
   modelFamily: "Anthropic Claude",
   maxInternalTokens: 1_000_000,
   contextWindow: 1_000_000,
   notableFeatures: ["1M token context", "Best for long conversations"],
   costPerMillionTokens: { input: 3.0, output: 15.0 },
 },
 "anthropic:claude-opus-4-1": {
   label: "Claude Opus 4.1",
   modelName: "anthropic:claude-opus-4-1",
   modelFamily: "Anthropic Claude",
   maxInternalTokens: 200_000,
   contextWindow: 200_000,
   notableFeatures: ["High accuracy", "Fast output"],
   costPerMillionTokens: { input: 15.0, output: 75.0 },
 },
 "openai:gpt-4o": {
   label: "GPT-4o",
   modelName: "openai:gpt-4o",
   modelFamily: "OpenAI GPT",
   maxInternalTokens: 128_000,
   contextWindow: 128_000,
   notableFeatures: ["Multimodal", "Fast inference"],
   costPerMillionTokens: { input: 2.5, output: 10.0 },
 },
 "google-genai:gemini-2.5-pro": {
   label: "Gemini 2.5 Pro",
   modelName: "google-genai:gemini-2.5-pro",
   modelFamily: "Google Gemini",
   maxInternalTokens: undefined,
   contextWindow: 1_048_576,
   notableFeatures: ["Multimodal", "1M token context window", "Integrated with Google products"],
   costPerMillionTokens: { input: 2.5, output: 15.0 },
 },
 "deepseek:v3.1": {
   label: "DeepSeek V3.1",
   modelName: "deepseek:v3.1",
   modelFamily: "DeepSeek",
   maxInternalTokens: 671_000_000,
   contextWindow: 128_000,
   notableFeatures: ["High-performance MoE", "Specialized in coding and reasoning"],
   costPerMillionTokens: { input: 0.14, output: 0.28 },
 },
 "qwen:3-1m": {
   label: "Qwen 3 (1M Context)",
   modelName: "qwen:3-1m",
   modelFamily: "Qwen",
   maxInternalTokens: 1_000_000,
   contextWindow: 1_000_000,
   notableFeatures: ["Ultra-long context", "Multilingual", "MoE architecture"],
   costPerMillionTokens: { input: 0.20, output: 0.60 },
 },
 "meta:llama-4-scout": {
   label: "Llama 4 Scout",
   modelName: "meta:llama-4-scout",
   modelFamily: "Meta Llama",
   maxInternalTokens: 109_000_000_000,
   contextWindow: 10_000_000,
   notableFeatures: ["10M context window", "Multimodal (text, image, video)", "Open-weight"],
   costPerMillionTokens: { input: 0.11, output: 0.34 },
 },
 "grok:4": {
   label: "Grok 4",
   modelName: "grok:4",
   modelFamily: "Grok",
   maxInternalTokens: undefined,
   contextWindow: 256_000,
   notableFeatures: ["Multimodal", "Real-time web searches", "Advanced reasoning"],
   costPerMillionTokens: { input: 3.0, output: 15.0 },
 },
 // Add other models here
};

// Utility to get model attributes
export function getMaxInternalTokensForModel(modelName: string): number {
 const model = MODEL_METADATA[modelName];
 if (!model) {
   throw new Error(`Unknown model: ${modelName}`);
 }
 return model.maxInternalTokens ?? model.contextWindow;
}

export function getModelMetadata(modelName: string): ModelMetadata {
 const model = MODEL_METADATA[modelName];
 if (!model) {
   throw new Error(`Unknown model: ${modelName}`);
 }
 return model;
}