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重构主控编排与运行时预热链路，统一工作区提示词/专家调度协议并补齐 wiki 记忆注入与写回闭环。

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同时收敛启动与运维脚本默认行为（含 wiki worker）、更新 Admin 可观测性与相关测试，降低首轮时延并提高运行稳定性。

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openclaw/extensions/vercel-ai-gateway/models.ts Normal file
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import type { ModelDefinitionConfig } from "openclaw/plugin-sdk/provider-model-shared";
import { createSubsystemLogger } from "openclaw/plugin-sdk/runtime-env";
export const VERCEL_AI_GATEWAY_PROVIDER_ID = "vercel-ai-gateway";
export const VERCEL_AI_GATEWAY_BASE_URL = "https://ai-gateway.vercel.sh";
export const VERCEL_AI_GATEWAY_DEFAULT_MODEL_ID = "anthropic/claude-opus-4.6";
export const VERCEL_AI_GATEWAY_DEFAULT_MODEL_REF = `${VERCEL_AI_GATEWAY_PROVIDER_ID}/${VERCEL_AI_GATEWAY_DEFAULT_MODEL_ID}`;
export const VERCEL_AI_GATEWAY_DEFAULT_CONTEXT_WINDOW = 200_000;
export const VERCEL_AI_GATEWAY_DEFAULT_MAX_TOKENS = 128_000;
export const VERCEL_AI_GATEWAY_DEFAULT_COST = {
input: 0,
output: 0,
cacheRead: 0,
cacheWrite: 0,
} as const;
const log = createSubsystemLogger("agents/vercel-ai-gateway");
type VercelPricingShape = {
input?: number | string;
output?: number | string;
input_cache_read?: number | string;
input_cache_write?: number | string;
};
type VercelGatewayModelShape = {
id?: string;
name?: string;
context_window?: number;
max_tokens?: number;
tags?: string[];
pricing?: VercelPricingShape;
};
type VercelGatewayModelsResponse = {
data?: VercelGatewayModelShape[];
};
type StaticVercelGatewayModel = Omit<ModelDefinitionConfig, "cost"> & {
cost?: Partial<ModelDefinitionConfig["cost"]>;
};
const STATIC_VERCEL_AI_GATEWAY_MODEL_CATALOG: readonly StaticVercelGatewayModel[] = [
{
id: "anthropic/claude-opus-4.6",
name: "Claude Opus 4.6",
reasoning: true,
input: ["text", "image"],
contextWindow: 1_000_000,
maxTokens: 128_000,
cost: {
input: 5,
output: 25,
cacheRead: 0.5,
cacheWrite: 6.25,
},
},
{
id: "openai/gpt-5.4",
name: "GPT 5.4",
reasoning: true,
input: ["text", "image"],
contextWindow: 200_000,
maxTokens: 128_000,
cost: {
input: 2.5,
output: 15,
cacheRead: 0.25,
},
},
{
id: "openai/gpt-5.4-pro",
name: "GPT 5.4 Pro",
reasoning: true,
input: ["text", "image"],
contextWindow: 200_000,
maxTokens: 128_000,
cost: {
input: 30,
output: 180,
cacheRead: 0,
},
},
] as const;
function toPerMillionCost(value: number | string | undefined): number {
const numeric =
typeof value === "number"
? value
: typeof value === "string"
? Number.parseFloat(value)
: Number.NaN;
if (!Number.isFinite(numeric) || numeric < 0) {
return 0;
}
return numeric * 1_000_000;
}
function normalizeCost(pricing?: VercelPricingShape): ModelDefinitionConfig["cost"] {
return {
input: toPerMillionCost(pricing?.input),
output: toPerMillionCost(pricing?.output),
cacheRead: toPerMillionCost(pricing?.input_cache_read),
cacheWrite: toPerMillionCost(pricing?.input_cache_write),
};
}
function buildStaticModelDefinition(model: StaticVercelGatewayModel): ModelDefinitionConfig {
return {
id: model.id,
name: model.name,
reasoning: model.reasoning,
input: model.input,
contextWindow: model.contextWindow,
maxTokens: model.maxTokens,
cost: {
...VERCEL_AI_GATEWAY_DEFAULT_COST,
...model.cost,
},
};
}
function getStaticFallbackModel(id: string): ModelDefinitionConfig | undefined {
const fallback = STATIC_VERCEL_AI_GATEWAY_MODEL_CATALOG.find((model) => model.id === id);
return fallback ? buildStaticModelDefinition(fallback) : undefined;
}
export function getStaticVercelAiGatewayModelCatalog(): ModelDefinitionConfig[] {
return STATIC_VERCEL_AI_GATEWAY_MODEL_CATALOG.map(buildStaticModelDefinition);
}
function buildDiscoveredModelDefinition(
model: VercelGatewayModelShape,
): ModelDefinitionConfig | null {
const id = typeof model.id === "string" ? model.id.trim() : "";
if (!id) {
return null;
}
const fallback = getStaticFallbackModel(id);
const contextWindow =
typeof model.context_window === "number" && Number.isFinite(model.context_window)
? model.context_window
: (fallback?.contextWindow ?? VERCEL_AI_GATEWAY_DEFAULT_CONTEXT_WINDOW);
const maxTokens =
typeof model.max_tokens === "number" && Number.isFinite(model.max_tokens)
? model.max_tokens
: (fallback?.maxTokens ?? VERCEL_AI_GATEWAY_DEFAULT_MAX_TOKENS);
const normalizedCost = normalizeCost(model.pricing);
return {
id,
name: (typeof model.name === "string" ? model.name.trim() : "") || fallback?.name || id,
reasoning:
Array.isArray(model.tags) && model.tags.includes("reasoning")
? true
: (fallback?.reasoning ?? false),
input: Array.isArray(model.tags)
? model.tags.includes("vision")
? ["text", "image"]
: ["text"]
: (fallback?.input ?? ["text"]),
contextWindow,
maxTokens,
cost:
normalizedCost.input > 0 ||
normalizedCost.output > 0 ||
normalizedCost.cacheRead > 0 ||
normalizedCost.cacheWrite > 0
? normalizedCost
: (fallback?.cost ?? VERCEL_AI_GATEWAY_DEFAULT_COST),
};
}
export async function discoverVercelAiGatewayModels(): Promise<ModelDefinitionConfig[]> {
if (process.env.VITEST || process.env.NODE_ENV === "test") {
return getStaticVercelAiGatewayModelCatalog();
}
try {
const response = await fetch(`${VERCEL_AI_GATEWAY_BASE_URL}/v1/models`, {
signal: AbortSignal.timeout(5000),
});
if (!response.ok) {
log.warn(`Failed to discover Vercel AI Gateway models: HTTP ${response.status}`);
return getStaticVercelAiGatewayModelCatalog();
}
const data = (await response.json()) as VercelGatewayModelsResponse;
const discovered = (data.data ?? [])
.map(buildDiscoveredModelDefinition)
.filter((entry): entry is ModelDefinitionConfig => entry !== null);
return discovered.length > 0 ? discovered : getStaticVercelAiGatewayModelCatalog();
} catch (error) {
log.warn(`Failed to discover Vercel AI Gateway models: ${String(error)}`);
return getStaticVercelAiGatewayModelCatalog();
}
}