mirror of https://github.com/buster-so/buster.git
Update AI SDK dependencies and refactor model initialization to use AI Gateway. Remove deprecated fallback logic and related tests for improved performance and maintainability.
This commit is contained in:
dal
parent
497598afe1
commit
d524e33996
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@ -38,10 +38,7 @@
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"braintrust:push:tools:staged": "npx braintrust push evals/agents/analyst-agent/tool-order/staged-scorers.ts"
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},
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"dependencies": {
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"@ai-sdk/anthropic": "^2.0.0",
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"@ai-sdk/google-vertex": "^3.0.0",
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"@ai-sdk/openai": "^2.0.0",
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"@ai-sdk/provider": "^2.0.0",
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"@ai-sdk/gateway": "^1.0.15",
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"@buster/access-controls": "workspace:*",
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"@buster/data-source": "workspace:*",
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"@buster/database": "workspace:*",
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File diff suppressed because it is too large
Load Diff
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@ -1,345 +0,0 @@
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import type {
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LanguageModelV2,
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LanguageModelV2CallOptions,
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LanguageModelV2CallWarning,
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LanguageModelV2Content,
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LanguageModelV2FinishReason,
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LanguageModelV2StreamPart,
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LanguageModelV2Usage,
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SharedV2ProviderMetadata,
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} from '@ai-sdk/provider';
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interface RetryableError extends Error {
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statusCode?: number;
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}
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interface Settings {
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models: LanguageModelV2[];
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retryAfterOutput?: boolean;
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modelResetInterval?: number;
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maxRetriesPerModel?: number;
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shouldRetryThisError?: (error: RetryableError) => boolean;
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onError?: (error: RetryableError, modelId: string) => void | Promise<void>;
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}
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export function createFallback(settings: Settings): FallbackModel {
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return new FallbackModel(settings);
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}
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const retryableStatusCodes = [
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401, // wrong API key
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403, // permission error, like cannot access model or from a non accessible region
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408, // request timeout
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409, // conflict
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413, // payload too large
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429, // too many requests/rate limits
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500, // server error (and above)
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];
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// Common error messages/codes that indicate server overload or temporary issues
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const retryableErrors = [
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'overloaded',
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'service unavailable',
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'bad gateway',
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'too many requests',
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'internal server error',
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'gateway timeout',
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'rate_limit',
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'wrong-key',
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'unexpected',
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'capacity',
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'timeout',
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'server_error',
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'429', // Too Many Requests
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'500', // Internal Server Error
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'502', // Bad Gateway
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'503', // Service Unavailable
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'504', // Gateway Timeout
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];
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function defaultShouldRetryThisError(error: RetryableError): boolean {
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// Handle null/undefined errors
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if (!error) return false;
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const statusCode = error.statusCode;
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if (statusCode && (retryableStatusCodes.includes(statusCode) || statusCode >= 500)) {
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return true;
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}
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if (error.message) {
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const errorString = error.message.toLowerCase();
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return retryableErrors.some((errType) => errorString.includes(errType));
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}
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// Check error object properties for retryable patterns
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if (typeof error === 'object') {
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try {
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const errorString = JSON.stringify(error).toLowerCase();
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return retryableErrors.some((errType) => errorString.includes(errType));
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} catch {
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// JSON.stringify can throw on circular references
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return false;
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}
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}
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return false;
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}
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function simpleBackoff(attempt: number): number {
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return Math.min(1000 * 2 ** attempt, 10000); // 1s, 2s, 4s, 8s, max 10s
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}
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export class FallbackModel implements LanguageModelV2 {
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readonly specificationVersion = 'v2';
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get supportedUrls(): Record<string, RegExp[]> | PromiseLike<Record<string, RegExp[]>> {
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return this.getCurrentModel().supportedUrls;
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}
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get modelId(): string {
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return this.getCurrentModel().modelId;
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}
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readonly settings: Settings;
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private _currentModelIndex = 0;
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private lastModelReset: number = Date.now();
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private readonly modelResetInterval: number;
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retryAfterOutput: boolean;
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get currentModelIndex(): number {
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return this._currentModelIndex;
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}
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private set currentModelIndex(value: number) {
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this._currentModelIndex = value;
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}
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constructor(settings: Settings) {
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this.settings = settings;
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this.modelResetInterval = settings.modelResetInterval ?? 3 * 60 * 1000; // Default 3 minutes in ms
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this.retryAfterOutput = settings.retryAfterOutput ?? true;
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if (!this.settings.models[this._currentModelIndex]) {
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throw new Error('No models available in settings');
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}
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}
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get provider(): string {
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return this.getCurrentModel().provider;
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}
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private getCurrentModel(): LanguageModelV2 {
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const model = this.settings.models[this._currentModelIndex];
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if (!model) {
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throw new Error(`No model available at index ${this._currentModelIndex}`);
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}
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console.info(
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`[Fallback] Using model: ${model.modelId} (index: ${this._currentModelIndex}/${this.settings.models.length - 1})`
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);
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return model;
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}
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private checkAndResetModel() {
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// Only reset if we're not already on the primary model
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if (this.currentModelIndex === 0) return;
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const now = Date.now();
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if (now - this.lastModelReset >= this.modelResetInterval) {
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// Reset to primary model
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console.info(
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`[Fallback] Resetting to primary model after ${this.modelResetInterval}ms timeout`
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);
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this.currentModelIndex = 0;
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this.lastModelReset = now;
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}
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}
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private switchToNextModel() {
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const previousModel = this.settings.models[this.currentModelIndex]?.modelId || 'unknown';
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this.currentModelIndex = (this.currentModelIndex + 1) % this.settings.models.length;
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const nextModel = this.settings.models[this.currentModelIndex]?.modelId || 'unknown';
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console.warn(`Switching from model ${previousModel} to ${nextModel} due to error`);
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}
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private async retry<T>(fn: () => PromiseLike<T>): Promise<T> {
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let lastError: RetryableError | undefined;
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const initialModel = this.currentModelIndex;
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const maxRetriesPerModel = this.settings.maxRetriesPerModel ?? 2;
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do {
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let modelRetryCount = 0;
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// Retry current model up to maxRetriesPerModel times
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while (modelRetryCount < maxRetriesPerModel) {
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try {
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const result = await fn();
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if (modelRetryCount > 0 || this.currentModelIndex !== initialModel) {
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console.info(
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`[Fallback] Request succeeded on model ${this.modelId} after ${modelRetryCount} retries`
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);
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}
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return result;
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} catch (error) {
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lastError = error as RetryableError;
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const shouldRetry = this.settings.shouldRetryThisError || defaultShouldRetryThisError;
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if (!shouldRetry(lastError)) {
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throw lastError; // Non-retryable error
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}
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if (this.settings.onError) {
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try {
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await this.settings.onError(lastError, this.modelId);
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} catch {
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// Don't let onError callback failures break the retry logic
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}
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}
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modelRetryCount++;
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if (modelRetryCount < maxRetriesPerModel) {
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// Wait before retrying same model
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await new Promise((resolve) => setTimeout(resolve, simpleBackoff(modelRetryCount - 1)));
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}
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}
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}
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// All retries for this model exhausted, switch to next model
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console.warn(
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`Model ${this.modelId} exhausted ${maxRetriesPerModel} retries, switching to next model`
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);
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this.switchToNextModel();
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if (this.currentModelIndex === initialModel) {
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throw lastError; // Tried all models
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}
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} while (this.currentModelIndex !== initialModel);
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// This should never be reached, but TypeScript requires it
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throw lastError || new Error('Retry failed');
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}
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doGenerate(options: LanguageModelV2CallOptions): PromiseLike<{
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content: LanguageModelV2Content[];
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finishReason: LanguageModelV2FinishReason;
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usage: LanguageModelV2Usage;
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providerMetadata?: SharedV2ProviderMetadata;
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request?: { body?: unknown };
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response?: {
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headers?: Record<string, string>;
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id?: string;
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timestamp?: Date;
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modelId?: string;
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};
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warnings: LanguageModelV2CallWarning[];
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}> {
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this.checkAndResetModel();
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return this.retry(() => this.getCurrentModel().doGenerate(options));
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}
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doStream(options: LanguageModelV2CallOptions): PromiseLike<{
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stream: ReadableStream<LanguageModelV2StreamPart>;
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request?: { body?: unknown };
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response?: { headers?: Record<string, string> };
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}> {
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this.checkAndResetModel();
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const self = this;
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const shouldRetry = this.settings.shouldRetryThisError || defaultShouldRetryThisError;
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console.info(`[Fallback] Starting stream request...`);
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return this.retry(async () => {
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const result = await self.getCurrentModel().doStream(options);
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let hasStreamedAny = false;
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// Wrap the stream to handle errors and switch providers if needed
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const wrappedStream = new ReadableStream<LanguageModelV2StreamPart>({
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async start(controller) {
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try {
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const reader = result.stream.getReader();
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let streamedChunks = 0;
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while (true) {
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const result = await reader.read();
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const { done, value } = result;
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if (!hasStreamedAny && value && typeof value === 'object' && 'error' in value) {
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const error = value.error as RetryableError;
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if (shouldRetry(error)) {
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throw error;
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}
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}
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if (done) {
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console.info(
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`[Fallback] Stream completed successfully. Streamed ${streamedChunks} chunks from ${self.modelId}`
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);
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break;
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}
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controller.enqueue(value);
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streamedChunks++;
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if (value?.type !== 'stream-start') {
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hasStreamedAny = true;
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}
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}
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controller.close();
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} catch (error) {
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// Check if this is a normal stream termination
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const errorMessage = error instanceof Error ? error.message : String(error);
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const isNormalTermination =
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errorMessage === 'terminated' ||
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errorMessage.includes('terminated') ||
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errorMessage === 'aborted' ||
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errorMessage.includes('aborted');
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// If it's a normal termination and we've already streamed content, just close normally
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if (isNormalTermination && hasStreamedAny) {
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controller.close();
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return;
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}
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if (self.settings.onError) {
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try {
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await self.settings.onError(error as RetryableError, self.modelId);
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} catch {
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// Don't let onError callback failures break the retry logic
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}
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}
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if (!hasStreamedAny || self.retryAfterOutput) {
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// If nothing was streamed yet, switch models and retry
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console.warn(`Stream error on ${self.modelId}, attempting fallback...`);
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self.switchToNextModel();
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// Prevent infinite recursion - if we've tried all models, fail
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if (self.currentModelIndex === 0) {
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console.error('All models exhausted, failing request');
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controller.error(error);
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return;
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}
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try {
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// Get the next model directly instead of recursive call
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const nextModel = self.getCurrentModel();
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const nextResult = await nextModel.doStream(options);
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const nextReader = nextResult.stream.getReader();
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while (true) {
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const { done, value } = await nextReader.read();
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if (done) break;
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controller.enqueue(value);
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}
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controller.close();
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} catch (nextError) {
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controller.error(nextError);
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}
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return;
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}
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controller.error(error);
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}
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},
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});
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return {
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stream: wrappedStream,
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...(result.request && { request: result.request }),
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...(result.response && { response: result.response }),
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};
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});
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}
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}
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@ -1,83 +1,4 @@
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import type { LanguageModelV2 } from '@ai-sdk/provider';
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import { createFallback } from './ai-fallback';
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import { openaiModel } from './providers/openai';
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import { gatewayModel } from './providers/gateway';
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// Lazy initialization to allow mocking in tests
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let _gpt5Instance: ReturnType<typeof createFallback> | null = null;
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function initializeGPT5() {
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if (_gpt5Instance) {
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return _gpt5Instance;
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}
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// Build models array based on available credentials
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const models: LanguageModelV2[] = [];
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// Only include OpenAI if API key is available
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if (process.env.OPENAI_API_KEY) {
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try {
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models.push(openaiModel('gpt-5-mini-2025-08-07'));
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console.info('GPT5: OpenAI model added to fallback chain');
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} catch (error) {
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console.warn('GPT5: Failed to initialize OpenAI model:', error);
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}
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}
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// Ensure we have at least one model
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if (models.length === 0) {
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throw new Error('No AI models available. Please set OPENAI_API_KEY environment variable.');
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}
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console.info(`GPT5: Initialized with ${models.length} model(s) in fallback chain`);
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_gpt5Instance = createFallback({
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models,
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modelResetInterval: 60000,
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retryAfterOutput: true,
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onError: (err, modelId) => {
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// Handle various error formats
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let errorMessage = 'Unknown error';
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if (err instanceof Error) {
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errorMessage = err.message;
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} else if (err && typeof err === 'object') {
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const errObj = err as Record<string, unknown>;
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if ('message' in errObj) {
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errorMessage = String(errObj.message);
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}
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if ('type' in errObj) {
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errorMessage = `${errObj.type}: ${errObj.message || 'No message'}`;
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}
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} else {
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errorMessage = String(err);
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}
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const errorDetails =
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err instanceof Error && err.stack ? err.stack : JSON.stringify(err, null, 2);
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console.error(`FALLBACK from model ${modelId}. Error: ${errorMessage}`);
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console.error('Error details:', errorDetails);
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},
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});
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return _gpt5Instance;
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}
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// Export a proxy that initializes on first use
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export const GPT5Mini = new Proxy({} as ReturnType<typeof createFallback>, {
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get(_target, prop) {
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const instance = initializeGPT5();
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// Direct property access without receiver to avoid proxy conflicts
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return instance[prop as keyof typeof instance];
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},
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has(_target, prop) {
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const instance = initializeGPT5();
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return prop in instance;
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},
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ownKeys(_target) {
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const instance = initializeGPT5();
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return Reflect.ownKeys(instance);
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},
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getOwnPropertyDescriptor(_target, prop) {
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const instance = initializeGPT5();
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return Reflect.getOwnPropertyDescriptor(instance, prop);
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},
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});
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// Export GPT-5 Mini model using AI Gateway
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export const GPT5Mini = gatewayModel('openai/gpt-5-mini-2025-08-07');
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|
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@ -1,83 +1,4 @@
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import type { LanguageModelV2 } from '@ai-sdk/provider';
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import { createFallback } from './ai-fallback';
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import { openaiModel } from './providers/openai';
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import { gatewayModel } from './providers/gateway';
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// Lazy initialization to allow mocking in tests
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let _gpt5Instance: ReturnType<typeof createFallback> | null = null;
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function initializeGPT5() {
|
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if (_gpt5Instance) {
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return _gpt5Instance;
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}
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// Build models array based on available credentials
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const models: LanguageModelV2[] = [];
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// Only include OpenAI if API key is available
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if (process.env.OPENAI_API_KEY) {
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try {
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models.push(openaiModel('gpt-5-nano-2025-08-07'));
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console.info('GPT5: OpenAI model added to fallback chain');
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} catch (error) {
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console.warn('GPT5: Failed to initialize OpenAI model:', error);
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}
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}
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// Ensure we have at least one model
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if (models.length === 0) {
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throw new Error('No AI models available. Please set OPENAI_API_KEY environment variable.');
|
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}
|
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|
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console.info(`GPT5: Initialized with ${models.length} model(s) in fallback chain`);
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_gpt5Instance = createFallback({
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models,
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modelResetInterval: 60000,
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retryAfterOutput: true,
|
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onError: (err, modelId) => {
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// Handle various error formats
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let errorMessage = 'Unknown error';
|
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if (err instanceof Error) {
|
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errorMessage = err.message;
|
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} else if (err && typeof err === 'object') {
|
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const errObj = err as Record<string, unknown>;
|
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if ('message' in errObj) {
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errorMessage = String(errObj.message);
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}
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if ('type' in errObj) {
|
||||
errorMessage = `${errObj.type}: ${errObj.message || 'No message'}`;
|
||||
}
|
||||
} else {
|
||||
errorMessage = String(err);
|
||||
}
|
||||
|
||||
const errorDetails =
|
||||
err instanceof Error && err.stack ? err.stack : JSON.stringify(err, null, 2);
|
||||
console.error(`FALLBACK from model ${modelId}. Error: ${errorMessage}`);
|
||||
console.error('Error details:', errorDetails);
|
||||
},
|
||||
});
|
||||
|
||||
return _gpt5Instance;
|
||||
}
|
||||
|
||||
// Export a proxy that initializes on first use
|
||||
export const GPT5Nano = new Proxy({} as ReturnType<typeof createFallback>, {
|
||||
get(_target, prop) {
|
||||
const instance = initializeGPT5();
|
||||
// Direct property access without receiver to avoid proxy conflicts
|
||||
return instance[prop as keyof typeof instance];
|
||||
},
|
||||
has(_target, prop) {
|
||||
const instance = initializeGPT5();
|
||||
return prop in instance;
|
||||
},
|
||||
ownKeys(_target) {
|
||||
const instance = initializeGPT5();
|
||||
return Reflect.ownKeys(instance);
|
||||
},
|
||||
getOwnPropertyDescriptor(_target, prop) {
|
||||
const instance = initializeGPT5();
|
||||
return Reflect.getOwnPropertyDescriptor(instance, prop);
|
||||
},
|
||||
});
|
||||
// Export GPT-5 Nano model using AI Gateway
|
||||
export const GPT5Nano = gatewayModel('openai/gpt-5-nano-2025-08-07');
|
||||
|
|
|
|||
|
|
@ -1,83 +1,4 @@
|
|||
import type { LanguageModelV2 } from '@ai-sdk/provider';
|
||||
import { createFallback } from './ai-fallback';
|
||||
import { openaiModel } from './providers/openai';
|
||||
import { gatewayModel } from './providers/gateway';
|
||||
|
||||
// Lazy initialization to allow mocking in tests
|
||||
let _gpt5Instance: ReturnType<typeof createFallback> | null = null;
|
||||
|
||||
function initializeGPT5() {
|
||||
if (_gpt5Instance) {
|
||||
return _gpt5Instance;
|
||||
}
|
||||
|
||||
// Build models array based on available credentials
|
||||
const models: LanguageModelV2[] = [];
|
||||
|
||||
// Only include OpenAI if API key is available
|
||||
if (process.env.OPENAI_API_KEY) {
|
||||
try {
|
||||
models.push(openaiModel('gpt-5-2025-08-07'));
|
||||
console.info('GPT5: OpenAI model added to fallback chain');
|
||||
} catch (error) {
|
||||
console.warn('GPT5: Failed to initialize OpenAI model:', error);
|
||||
}
|
||||
}
|
||||
|
||||
// Ensure we have at least one model
|
||||
if (models.length === 0) {
|
||||
throw new Error('No AI models available. Please set OPENAI_API_KEY environment variable.');
|
||||
}
|
||||
|
||||
console.info(`GPT5: Initialized with ${models.length} model(s) in fallback chain`);
|
||||
|
||||
_gpt5Instance = createFallback({
|
||||
models,
|
||||
modelResetInterval: 60000,
|
||||
retryAfterOutput: true,
|
||||
onError: (err, modelId) => {
|
||||
// Handle various error formats
|
||||
let errorMessage = 'Unknown error';
|
||||
if (err instanceof Error) {
|
||||
errorMessage = err.message;
|
||||
} else if (err && typeof err === 'object') {
|
||||
const errObj = err as Record<string, unknown>;
|
||||
if ('message' in errObj) {
|
||||
errorMessage = String(errObj.message);
|
||||
}
|
||||
if ('type' in errObj) {
|
||||
errorMessage = `${errObj.type}: ${errObj.message || 'No message'}`;
|
||||
}
|
||||
} else {
|
||||
errorMessage = String(err);
|
||||
}
|
||||
|
||||
const errorDetails =
|
||||
err instanceof Error && err.stack ? err.stack : JSON.stringify(err, null, 2);
|
||||
console.error(`FALLBACK from model ${modelId}. Error: ${errorMessage}`);
|
||||
console.error('Error details:', errorDetails);
|
||||
},
|
||||
});
|
||||
|
||||
return _gpt5Instance;
|
||||
}
|
||||
|
||||
// Export a proxy that initializes on first use
|
||||
export const GPT5 = new Proxy({} as ReturnType<typeof createFallback>, {
|
||||
get(_target, prop) {
|
||||
const instance = initializeGPT5();
|
||||
// Direct property access without receiver to avoid proxy conflicts
|
||||
return instance[prop as keyof typeof instance];
|
||||
},
|
||||
has(_target, prop) {
|
||||
const instance = initializeGPT5();
|
||||
return prop in instance;
|
||||
},
|
||||
ownKeys(_target) {
|
||||
const instance = initializeGPT5();
|
||||
return Reflect.ownKeys(instance);
|
||||
},
|
||||
getOwnPropertyDescriptor(_target, prop) {
|
||||
const instance = initializeGPT5();
|
||||
return Reflect.getOwnPropertyDescriptor(instance, prop);
|
||||
},
|
||||
});
|
||||
// Export GPT-5 model using AI Gateway
|
||||
export const GPT5 = gatewayModel('openai/gpt-5-2025-08-07');
|
||||
|
|
|
|||
|
|
@ -1,108 +1,4 @@
|
|||
import type { LanguageModelV2 } from '@ai-sdk/provider';
|
||||
import { createFallback } from './ai-fallback';
|
||||
import { anthropicModel } from './providers/anthropic';
|
||||
import { vertexModel } from './providers/vertex';
|
||||
import { gatewayModel } from './providers/gateway';
|
||||
|
||||
// Lazy initialization to allow mocking in tests
|
||||
let _haiku35Instance: ReturnType<typeof createFallback> | null = null;
|
||||
|
||||
function initializeHaiku35() {
|
||||
if (_haiku35Instance) {
|
||||
return _haiku35Instance;
|
||||
}
|
||||
|
||||
// Build models array based on available credentials
|
||||
const models: LanguageModelV2[] = [];
|
||||
|
||||
// Only include Anthropic if API key is available
|
||||
if (process.env.ANTHROPIC_API_KEY) {
|
||||
try {
|
||||
models.push(anthropicModel('claude-3-5-haiku-20241022'));
|
||||
console.info('Haiku35: Anthropic model added to fallback chain');
|
||||
} catch (error) {
|
||||
console.warn('Haiku35: Failed to initialize Anthropic model:', error);
|
||||
}
|
||||
}
|
||||
|
||||
// Only include Vertex if all required credentials are available
|
||||
if (
|
||||
process.env.VERTEX_CLIENT_EMAIL &&
|
||||
process.env.VERTEX_PRIVATE_KEY &&
|
||||
process.env.VERTEX_PROJECT
|
||||
) {
|
||||
try {
|
||||
models.push(vertexModel('claude-3-5-haiku@20241022'));
|
||||
console.info('Haiku35: Vertex AI model added to fallback chain (fallback)');
|
||||
} catch (error) {
|
||||
console.warn('Haiku35: Failed to initialize Vertex AI model:', error);
|
||||
}
|
||||
} else {
|
||||
const missing = [];
|
||||
if (!process.env.VERTEX_CLIENT_EMAIL) missing.push('VERTEX_CLIENT_EMAIL');
|
||||
if (!process.env.VERTEX_PRIVATE_KEY) missing.push('VERTEX_PRIVATE_KEY');
|
||||
if (!process.env.VERTEX_PROJECT) missing.push('VERTEX_PROJECT');
|
||||
console.info(
|
||||
`Haiku35: Missing Vertex credentials (${missing.join(', ')}), skipping Vertex model`
|
||||
);
|
||||
}
|
||||
|
||||
// Ensure we have at least one model
|
||||
if (models.length === 0) {
|
||||
throw new Error(
|
||||
'No AI models available. Please set either Vertex AI (VERTEX_CLIENT_EMAIL and VERTEX_PRIVATE_KEY) or Anthropic (ANTHROPIC_API_KEY) credentials.'
|
||||
);
|
||||
}
|
||||
|
||||
console.info(`Haiku35: Initialized with ${models.length} model(s) in fallback chain`);
|
||||
|
||||
_haiku35Instance = createFallback({
|
||||
models,
|
||||
modelResetInterval: 60000,
|
||||
retryAfterOutput: true,
|
||||
onError: (err, modelId) => {
|
||||
// Handle various error formats
|
||||
let errorMessage = 'Unknown error';
|
||||
if (err instanceof Error) {
|
||||
errorMessage = err.message;
|
||||
} else if (err && typeof err === 'object') {
|
||||
const errObj = err as Record<string, unknown>;
|
||||
if ('message' in errObj) {
|
||||
errorMessage = String(errObj.message);
|
||||
}
|
||||
if ('type' in errObj) {
|
||||
errorMessage = `${errObj.type}: ${errObj.message || 'No message'}`;
|
||||
}
|
||||
} else {
|
||||
errorMessage = String(err);
|
||||
}
|
||||
|
||||
const errorDetails =
|
||||
err instanceof Error && err.stack ? err.stack : JSON.stringify(err, null, 2);
|
||||
console.error(`FALLBACK from model ${modelId}. Error: ${errorMessage}`);
|
||||
console.error('Error details:', errorDetails);
|
||||
},
|
||||
});
|
||||
|
||||
return _haiku35Instance;
|
||||
}
|
||||
|
||||
// Export a proxy that initializes on first use
|
||||
export const Haiku35 = new Proxy({} as ReturnType<typeof createFallback>, {
|
||||
get(_target, prop) {
|
||||
const instance = initializeHaiku35();
|
||||
// Direct property access without receiver to avoid proxy conflicts
|
||||
return instance[prop as keyof typeof instance];
|
||||
},
|
||||
has(_target, prop) {
|
||||
const instance = initializeHaiku35();
|
||||
return prop in instance;
|
||||
},
|
||||
ownKeys(_target) {
|
||||
const instance = initializeHaiku35();
|
||||
return Reflect.ownKeys(instance);
|
||||
},
|
||||
getOwnPropertyDescriptor(_target, prop) {
|
||||
const instance = initializeHaiku35();
|
||||
return Reflect.getOwnPropertyDescriptor(instance, prop);
|
||||
},
|
||||
});
|
||||
// Export Haiku 3.5 model using AI Gateway
|
||||
export const Haiku35 = gatewayModel('anthropic/claude-3-5-haiku-20241022');
|
||||
|
|
|
|||
|
|
@ -1,65 +1,4 @@
|
|||
import type { LanguageModelV2 } from '@ai-sdk/provider';
|
||||
import { createFallback } from './ai-fallback';
|
||||
import { anthropicModel } from './providers/anthropic';
|
||||
import { vertexModel } from './providers/vertex';
|
||||
import { gatewayModel } from './providers/gateway';
|
||||
|
||||
// Lazy initialization to allow mocking in tests
|
||||
let _opus41Instance: ReturnType<typeof createFallback> | null = null;
|
||||
|
||||
function initializeOpus41() {
|
||||
if (_opus41Instance) {
|
||||
return _opus41Instance;
|
||||
}
|
||||
|
||||
// Build models array based on available credentials
|
||||
const models: LanguageModelV2[] = [];
|
||||
|
||||
// Only include Anthropic if API key is available
|
||||
if (process.env.ANTHROPIC_API_KEY) {
|
||||
try {
|
||||
models.push(anthropicModel('claude-opus-4-1-20250805'));
|
||||
console.info('Opus41: Anthropic model added to fallback chain');
|
||||
} catch (error) {
|
||||
console.warn('Opus41: Failed to initialize Anthropic model:', error);
|
||||
}
|
||||
}
|
||||
|
||||
// Ensure we have at least one model
|
||||
if (models.length === 0) {
|
||||
throw new Error(
|
||||
'No AI models available. Please set either Vertex AI (VERTEX_CLIENT_EMAIL and VERTEX_PRIVATE_KEY) or Anthropic (ANTHROPIC_API_KEY) credentials.'
|
||||
);
|
||||
}
|
||||
|
||||
console.info(`Opus41: Initialized with ${models.length} model(s) in fallback chain`);
|
||||
|
||||
_opus41Instance = createFallback({
|
||||
models,
|
||||
modelResetInterval: 60000,
|
||||
retryAfterOutput: true,
|
||||
onError: (err) => console.error(`FALLBACK. Here is the error: ${err}`),
|
||||
});
|
||||
|
||||
return _opus41Instance;
|
||||
}
|
||||
|
||||
// Export a proxy that initializes on first use
|
||||
export const Opus41 = new Proxy({} as ReturnType<typeof createFallback>, {
|
||||
get(_target, prop) {
|
||||
const instance = initializeOpus41();
|
||||
// Direct property access without receiver to avoid proxy conflicts
|
||||
return instance[prop as keyof typeof instance];
|
||||
},
|
||||
has(_target, prop) {
|
||||
const instance = initializeOpus41();
|
||||
return prop in instance;
|
||||
},
|
||||
ownKeys(_target) {
|
||||
const instance = initializeOpus41();
|
||||
return Reflect.ownKeys(instance);
|
||||
},
|
||||
getOwnPropertyDescriptor(_target, prop) {
|
||||
const instance = initializeOpus41();
|
||||
return Reflect.getOwnPropertyDescriptor(instance, prop);
|
||||
},
|
||||
});
|
||||
// Export Opus 4.1 model using AI Gateway
|
||||
export const Opus41 = gatewayModel('anthropic/claude-opus-4-1-20250805');
|
||||
|
|
|
|||
|
|
@ -1,51 +0,0 @@
|
|||
import { createAnthropic } from '@ai-sdk/anthropic';
|
||||
import { wrapLanguageModel } from 'ai';
|
||||
import { BraintrustMiddleware } from 'braintrust';
|
||||
|
||||
export const anthropicModel = (modelId: string) => {
|
||||
const anthropic = createAnthropic({
|
||||
headers: {
|
||||
'anthropic-beta': 'fine-grained-tool-streaming-2025-05-14,extended-cache-ttl-2025-04-11',
|
||||
},
|
||||
fetch: ((url, options) => {
|
||||
if (options?.body) {
|
||||
try {
|
||||
// Parse existing body if it's a string
|
||||
const existingBody =
|
||||
typeof options.body === 'string' ? JSON.parse(options.body) : options.body;
|
||||
|
||||
// Append disable_parallel_tool_use if tool_choice is present
|
||||
const modifiedBody = {
|
||||
...existingBody,
|
||||
};
|
||||
|
||||
if (modifiedBody.tool_choice) {
|
||||
modifiedBody.tool_choice = {
|
||||
...modifiedBody.tool_choice,
|
||||
disable_parallel_tool_use: true,
|
||||
};
|
||||
}
|
||||
|
||||
// Return modified options
|
||||
return fetch(url, {
|
||||
...options,
|
||||
body: JSON.stringify(modifiedBody),
|
||||
});
|
||||
} catch (error) {
|
||||
console.error('Failed to parse request body:', error);
|
||||
// If body parsing fails, fall back to original request
|
||||
return fetch(url, options);
|
||||
}
|
||||
}
|
||||
|
||||
// For requests without body, pass through unchanged
|
||||
return fetch(url, options);
|
||||
}) as typeof fetch,
|
||||
});
|
||||
|
||||
// Wrap the model with Braintrust middleware
|
||||
return wrapLanguageModel({
|
||||
model: anthropic(modelId),
|
||||
middleware: BraintrustMiddleware({ debug: true }),
|
||||
});
|
||||
};
|
||||
|
|
@ -0,0 +1,69 @@
|
|||
import { createGateway } from '@ai-sdk/gateway';
|
||||
import { wrapLanguageModel } from 'ai';
|
||||
import { BraintrustMiddleware } from 'braintrust';
|
||||
|
||||
// Create gateway instance with custom fetch for Anthropic headers
|
||||
const gateway = createGateway({
|
||||
...(process.env.AI_GATEWAY_API_KEY && { apiKey: process.env.AI_GATEWAY_API_KEY }),
|
||||
// Custom fetch to inject Anthropic beta headers when needed
|
||||
fetch: ((url, options) => {
|
||||
// Check if this is an Anthropic request
|
||||
if (typeof url === 'string' && url.includes('anthropic')) {
|
||||
// Parse and modify the request body to add disable_parallel_tool_use
|
||||
if (options?.body) {
|
||||
try {
|
||||
const existingBody =
|
||||
typeof options.body === 'string' ? JSON.parse(options.body) : options.body;
|
||||
|
||||
const modifiedBody = { ...existingBody };
|
||||
if (modifiedBody.tool_choice) {
|
||||
modifiedBody.tool_choice = {
|
||||
...modifiedBody.tool_choice,
|
||||
disable_parallel_tool_use: true,
|
||||
};
|
||||
}
|
||||
|
||||
// Add Anthropic beta headers
|
||||
const headers = {
|
||||
...options.headers,
|
||||
'anthropic-beta':
|
||||
'fine-grained-tool-streaming-2025-05-14,extended-cache-ttl-2025-04-11',
|
||||
};
|
||||
|
||||
return fetch(url, {
|
||||
...options,
|
||||
headers,
|
||||
body: JSON.stringify(modifiedBody),
|
||||
});
|
||||
} catch (error) {
|
||||
console.error('Failed to parse request body:', error);
|
||||
// If parsing fails, still add headers but don't modify body
|
||||
const headers = {
|
||||
...options.headers,
|
||||
'anthropic-beta':
|
||||
'fine-grained-tool-streaming-2025-05-14,extended-cache-ttl-2025-04-11',
|
||||
};
|
||||
return fetch(url, { ...options, headers });
|
||||
}
|
||||
}
|
||||
|
||||
// For requests without body, just add headers
|
||||
const headers = {
|
||||
...(options?.headers || {}),
|
||||
'anthropic-beta': 'fine-grained-tool-streaming-2025-05-14,extended-cache-ttl-2025-04-11',
|
||||
};
|
||||
return fetch(url, { ...options, headers });
|
||||
}
|
||||
|
||||
// For non-Anthropic requests, pass through unchanged
|
||||
return fetch(url, options);
|
||||
}) as typeof fetch,
|
||||
});
|
||||
|
||||
// Export a function that creates wrapped models with Braintrust middleware
|
||||
export const gatewayModel = (modelId: string) => {
|
||||
return wrapLanguageModel({
|
||||
model: gateway(modelId),
|
||||
middleware: BraintrustMiddleware({ debug: true }),
|
||||
});
|
||||
};
|
||||
|
|
@ -1,15 +0,0 @@
|
|||
import { createOpenAI } from '@ai-sdk/openai';
|
||||
import { wrapLanguageModel } from 'ai';
|
||||
import { BraintrustMiddleware } from 'braintrust';
|
||||
|
||||
export const openaiModel = (modelId: string) => {
|
||||
const openai = createOpenAI({
|
||||
apiKey: process.env.OPENAI_API_KEY,
|
||||
});
|
||||
|
||||
// Wrap the model with Braintrust middleware
|
||||
return wrapLanguageModel({
|
||||
model: openai(modelId),
|
||||
middleware: BraintrustMiddleware({ debug: true }),
|
||||
});
|
||||
};
|
||||
|
|
@ -1,90 +0,0 @@
|
|||
import { createVertexAnthropic } from '@ai-sdk/google-vertex/anthropic';
|
||||
import type { LanguageModelV2 } from '@ai-sdk/provider';
|
||||
import { wrapLanguageModel } from 'ai';
|
||||
import { BraintrustMiddleware } from 'braintrust';
|
||||
|
||||
export const vertexModel = (modelId: string): LanguageModelV2 => {
|
||||
// Create a proxy that validates credentials on first use
|
||||
let actualModel: LanguageModelV2 | null = null;
|
||||
|
||||
const getActualModel = () => {
|
||||
if (!actualModel) {
|
||||
const clientEmail = process.env.VERTEX_CLIENT_EMAIL;
|
||||
let privateKey = process.env.VERTEX_PRIVATE_KEY;
|
||||
const project = process.env.VERTEX_PROJECT;
|
||||
|
||||
if (!clientEmail || !privateKey || !project) {
|
||||
throw new Error(
|
||||
'Missing required environment variables: VERTEX_CLIENT_EMAIL or VERTEX_PRIVATE_KEY'
|
||||
);
|
||||
}
|
||||
|
||||
// Handle escaped newlines in private key
|
||||
privateKey = privateKey.replace(/\\n/g, '\n');
|
||||
|
||||
const vertex = createVertexAnthropic({
|
||||
baseURL: `https://aiplatform.googleapis.com/v1/projects/${project}/locations/global/publishers/anthropic/models`,
|
||||
location: 'global',
|
||||
project,
|
||||
googleAuthOptions: {
|
||||
credentials: {
|
||||
client_email: clientEmail,
|
||||
private_key: privateKey,
|
||||
},
|
||||
},
|
||||
headers: {
|
||||
'anthropic-beta': 'fine-grained-tool-streaming-2025-05-14,extended-cache-ttl-2025-04-11',
|
||||
},
|
||||
fetch: ((url, options) => {
|
||||
if (options?.body) {
|
||||
try {
|
||||
// Parse existing body if it's a string
|
||||
const existingBody =
|
||||
typeof options.body === 'string' ? JSON.parse(options.body) : options.body;
|
||||
|
||||
// Append disable_parallel_tool_use if tool_choice is present
|
||||
const modifiedBody = {
|
||||
...existingBody,
|
||||
};
|
||||
|
||||
if (modifiedBody.tool_choice) {
|
||||
modifiedBody.tool_choice = {
|
||||
...modifiedBody.tool_choice,
|
||||
disable_parallel_tool_use: true,
|
||||
};
|
||||
}
|
||||
|
||||
// Return modified options
|
||||
return fetch(url, {
|
||||
...options,
|
||||
body: JSON.stringify(modifiedBody),
|
||||
});
|
||||
} catch (error) {
|
||||
console.error('Failed to parse request body:', error);
|
||||
// If body parsing fails, fall back to original request
|
||||
return fetch(url, options);
|
||||
}
|
||||
}
|
||||
|
||||
// For requests without body, pass through unchanged
|
||||
return fetch(url, options);
|
||||
}) as typeof fetch,
|
||||
});
|
||||
|
||||
// Wrap the model with Braintrust middleware
|
||||
actualModel = wrapLanguageModel({
|
||||
model: vertex(modelId),
|
||||
middleware: BraintrustMiddleware({ debug: true }),
|
||||
});
|
||||
}
|
||||
return actualModel;
|
||||
};
|
||||
|
||||
// Create a proxy that delegates all calls to the actual model
|
||||
return new Proxy({} as LanguageModelV2, {
|
||||
get(_target, prop) {
|
||||
const model = getActualModel();
|
||||
return Reflect.get(model, prop);
|
||||
},
|
||||
});
|
||||
};
|
||||
|
|
@ -1,99 +1,4 @@
|
|||
import type { LanguageModelV2 } from '@ai-sdk/provider';
|
||||
import { createFallback } from './ai-fallback';
|
||||
import { anthropicModel } from './providers/anthropic';
|
||||
import { openaiModel } from './providers/openai';
|
||||
import { vertexModel } from './providers/vertex';
|
||||
import { gatewayModel } from './providers/gateway';
|
||||
|
||||
// Lazy initialization to allow mocking in tests
|
||||
let _sonnet4Instance: ReturnType<typeof createFallback> | null = null;
|
||||
|
||||
function initializeSonnet4(): ReturnType<typeof createFallback> {
|
||||
if (_sonnet4Instance) {
|
||||
return _sonnet4Instance;
|
||||
}
|
||||
|
||||
// Build models array based on available credentials
|
||||
const models: LanguageModelV2[] = [];
|
||||
|
||||
// Only include Anthropic if API key is available
|
||||
if (process.env.ANTHROPIC_API_KEY) {
|
||||
try {
|
||||
models.push(anthropicModel('claude-4-sonnet-20250514'));
|
||||
console.info('Sonnet4: Anthropic model added to fallback chain (primary)');
|
||||
} catch (error) {
|
||||
console.warn('Sonnet4: Failed to initialize Anthropic model:', error);
|
||||
}
|
||||
} else {
|
||||
console.info('Sonnet4: No ANTHROPIC_API_KEY found, skipping Anthropic model');
|
||||
}
|
||||
|
||||
if (process.env.OPENAI_API_KEY) {
|
||||
try {
|
||||
models.push(openaiModel('gpt-5'));
|
||||
|
||||
console.info('Sonnet4: OpenAI model added to fallback chain');
|
||||
} catch (error) {
|
||||
console.warn('Sonnet4: Failed to initialize OpenAI model:', error);
|
||||
}
|
||||
}
|
||||
|
||||
// Ensure we have at least one model
|
||||
if (models.length === 0) {
|
||||
throw new Error(
|
||||
'No AI models available. Please set either Vertex AI (VERTEX_CLIENT_EMAIL and VERTEX_PRIVATE_KEY) or Anthropic (ANTHROPIC_API_KEY) credentials.'
|
||||
);
|
||||
}
|
||||
|
||||
console.info(`Sonnet4: Initialized with ${models.length} model(s) in fallback chain`);
|
||||
|
||||
_sonnet4Instance = createFallback({
|
||||
models,
|
||||
modelResetInterval: 60000,
|
||||
retryAfterOutput: true,
|
||||
onError: (err, modelId) => {
|
||||
// Handle various error formats
|
||||
let errorMessage = 'Unknown error';
|
||||
if (err instanceof Error) {
|
||||
errorMessage = err.message;
|
||||
} else if (err && typeof err === 'object') {
|
||||
const errObj = err as Record<string, unknown>;
|
||||
if ('message' in errObj) {
|
||||
errorMessage = String(errObj.message);
|
||||
}
|
||||
if ('type' in errObj) {
|
||||
errorMessage = `${errObj.type}: ${errObj.message || 'No message'}`;
|
||||
}
|
||||
} else {
|
||||
errorMessage = String(err);
|
||||
}
|
||||
|
||||
const errorDetails =
|
||||
err instanceof Error && err.stack ? err.stack : JSON.stringify(err, null, 2);
|
||||
console.error(`FALLBACK from model ${modelId}. Error: ${errorMessage}`);
|
||||
console.error('Error details:', errorDetails);
|
||||
},
|
||||
});
|
||||
|
||||
return _sonnet4Instance;
|
||||
}
|
||||
|
||||
// Export a proxy that initializes on first use
|
||||
export const Sonnet4 = new Proxy({} as ReturnType<typeof createFallback>, {
|
||||
get(_target, prop) {
|
||||
const instance = initializeSonnet4();
|
||||
// Direct property access without receiver to avoid proxy conflicts
|
||||
return instance[prop as keyof typeof instance];
|
||||
},
|
||||
has(_target, prop) {
|
||||
const instance = initializeSonnet4();
|
||||
return prop in instance;
|
||||
},
|
||||
ownKeys(_target) {
|
||||
const instance = initializeSonnet4();
|
||||
return Reflect.ownKeys(instance);
|
||||
},
|
||||
getOwnPropertyDescriptor(_target, prop) {
|
||||
const instance = initializeSonnet4();
|
||||
return Reflect.getOwnPropertyDescriptor(instance, prop);
|
||||
},
|
||||
});
|
||||
// Export Sonnet 4 model using AI Gateway
|
||||
export const Sonnet4 = gatewayModel('anthropic/claude-4-sonnet-20250514');
|
||||
|
|
|
|||
|
|
@ -877,6 +877,9 @@ importers:
|
|||
'@ai-sdk/anthropic':
|
||||
specifier: ^2.0.0
|
||||
version: 2.0.1(zod@3.25.76)
|
||||
'@ai-sdk/gateway':
|
||||
specifier: ^1.0.15
|
||||
version: 1.0.15(zod@3.25.76)
|
||||
'@ai-sdk/google-vertex':
|
||||
specifier: ^3.0.0
|
||||
version: 3.0.3(zod@3.25.76)
|
||||
|
|
@ -1248,6 +1251,12 @@ packages:
|
|||
peerDependencies:
|
||||
zod: ^3.25.76 || ^4
|
||||
|
||||
'@ai-sdk/gateway@1.0.15':
|
||||
resolution: {integrity: sha512-xySXoQ29+KbGuGfmDnABx+O6vc7Gj7qugmj1kGpn0rW0rQNn6UKUuvscKMzWyv1Uv05GyC1vqHq8ZhEOLfXscQ==}
|
||||
engines: {node: '>=18'}
|
||||
peerDependencies:
|
||||
zod: ^3.25.76 || ^4
|
||||
|
||||
'@ai-sdk/gateway@1.0.3':
|
||||
resolution: {integrity: sha512-QRGz2vH1WR9NvCv8gWocoebAKiXcuqj22mug6i8COeVsp33x5K5cK2DT4TwiQx5SfYbqJbVoBT+UqnHF7A3PHA==}
|
||||
engines: {node: '>=18'}
|
||||
|
|
@ -1290,6 +1299,12 @@ packages:
|
|||
peerDependencies:
|
||||
zod: ^3.25.76 || ^4
|
||||
|
||||
'@ai-sdk/provider-utils@3.0.7':
|
||||
resolution: {integrity: sha512-o3BS5/t8KnBL3ubP8k3w77AByOypLm+pkIL/DCw0qKkhDbvhCy+L3hRTGPikpdb8WHcylAeKsjgwOxhj4cqTUA==}
|
||||
engines: {node: '>=18'}
|
||||
peerDependencies:
|
||||
zod: ^3.25.76 || ^4
|
||||
|
||||
'@ai-sdk/provider@1.1.3':
|
||||
resolution: {integrity: sha512-qZMxYJ0qqX/RfnuIaab+zp8UAeJn/ygXXAffR5I4N0n1IrvA6qBsjc8hXLmBiMV2zoXlifkacF7sEFnYnjBcqg==}
|
||||
engines: {node: '>=18'}
|
||||
|
|
@ -7620,6 +7635,10 @@ packages:
|
|||
resolution: {integrity: sha512-nVpZkTMM9rF6AQ9gPJpFsNAMt48wIzB5TQgiTLdHiuO8XEDhUgZEhqKlZWXbIzo9VmJ/HvysHqEaVeD5v9TPvA==}
|
||||
engines: {node: '>=20.0.0'}
|
||||
|
||||
eventsource-parser@3.0.6:
|
||||
resolution: {integrity: sha512-Vo1ab+QXPzZ4tCa8SwIHJFaSzy4R6SHf7BY79rFBDf0idraZWAkYrDjDj8uWaSm3S2TK+hJ7/t1CEmZ7jXw+pg==}
|
||||
engines: {node: '>=18.0.0'}
|
||||
|
||||
eventsource@3.0.7:
|
||||
resolution: {integrity: sha512-CRT1WTyuQoD771GW56XEZFQ/ZoSfWid1alKGDYMmkt2yl8UXrVR4pspqWNEcqKvVIzg6PAltWjxcSSPrboA4iA==}
|
||||
engines: {node: '>=18.0.0'}
|
||||
|
|
@ -12325,6 +12344,12 @@ snapshots:
|
|||
'@ai-sdk/provider-utils': 3.0.1(zod@3.25.76)
|
||||
zod: 3.25.76
|
||||
|
||||
'@ai-sdk/gateway@1.0.15(zod@3.25.76)':
|
||||
dependencies:
|
||||
'@ai-sdk/provider': 2.0.0
|
||||
'@ai-sdk/provider-utils': 3.0.7(zod@3.25.76)
|
||||
zod: 3.25.76
|
||||
|
||||
'@ai-sdk/gateway@1.0.3(zod@3.25.1)':
|
||||
dependencies:
|
||||
'@ai-sdk/provider': 2.0.0
|
||||
|
|
@ -12391,6 +12416,13 @@ snapshots:
|
|||
zod: 3.25.76
|
||||
zod-to-json-schema: 3.24.6(zod@3.25.76)
|
||||
|
||||
'@ai-sdk/provider-utils@3.0.7(zod@3.25.76)':
|
||||
dependencies:
|
||||
'@ai-sdk/provider': 2.0.0
|
||||
'@standard-schema/spec': 1.0.0
|
||||
eventsource-parser: 3.0.6
|
||||
zod: 3.25.76
|
||||
|
||||
'@ai-sdk/provider@1.1.3':
|
||||
dependencies:
|
||||
json-schema: 0.4.0
|
||||
|
|
@ -18323,14 +18355,14 @@ snapshots:
|
|||
msw: 2.10.4(@types/node@20.19.4)(typescript@5.9.2)
|
||||
vite: 7.0.5(@types/node@20.19.4)(jiti@2.4.2)(lightningcss@1.30.1)(sass@1.90.0)(terser@5.43.1)(tsx@4.20.4)(yaml@2.8.0)
|
||||
|
||||
'@vitest/mocker@3.2.4(msw@2.10.4(@types/node@24.0.10)(typescript@5.9.2))(vite@7.0.5(@types/node@20.19.4)(jiti@2.4.2)(lightningcss@1.30.1)(sass@1.90.0)(terser@5.43.1)(tsx@4.20.4)(yaml@2.8.0))':
|
||||
'@vitest/mocker@3.2.4(msw@2.10.4(@types/node@24.0.10)(typescript@5.9.2))(vite@7.0.5(@types/node@24.0.10)(jiti@2.4.2)(lightningcss@1.30.1)(sass@1.90.0)(terser@5.43.1)(tsx@4.20.4)(yaml@2.8.0))':
|
||||
dependencies:
|
||||
'@vitest/spy': 3.2.4
|
||||
estree-walker: 3.0.3
|
||||
magic-string: 0.30.17
|
||||
optionalDependencies:
|
||||
msw: 2.10.4(@types/node@24.0.10)(typescript@5.9.2)
|
||||
vite: 7.0.5(@types/node@20.19.4)(jiti@2.4.2)(lightningcss@1.30.1)(sass@1.90.0)(terser@5.43.1)(tsx@4.20.4)(yaml@2.8.0)
|
||||
vite: 7.0.5(@types/node@24.0.10)(jiti@2.4.2)(lightningcss@1.30.1)(sass@1.90.0)(terser@5.43.1)(tsx@4.20.4)(yaml@2.8.0)
|
||||
|
||||
'@vitest/mocker@3.2.4(msw@2.10.4(@types/node@24.0.10)(typescript@5.9.2))(vite@7.1.3(@types/node@24.0.10)(jiti@2.4.2)(lightningcss@1.30.1)(sass@1.90.0)(terser@5.43.1)(tsx@4.20.4)(yaml@2.8.0))':
|
||||
dependencies:
|
||||
|
|
@ -20420,6 +20452,8 @@ snapshots:
|
|||
|
||||
eventsource-parser@3.0.3: {}
|
||||
|
||||
eventsource-parser@3.0.6: {}
|
||||
|
||||
eventsource@3.0.7:
|
||||
dependencies:
|
||||
eventsource-parser: 3.0.3
|
||||
|
|
@ -25525,7 +25559,7 @@ snapshots:
|
|||
dependencies:
|
||||
'@types/chai': 5.2.2
|
||||
'@vitest/expect': 3.2.4
|
||||
'@vitest/mocker': 3.2.4(msw@2.10.4(@types/node@24.0.10)(typescript@5.9.2))(vite@7.0.5(@types/node@20.19.4)(jiti@2.4.2)(lightningcss@1.30.1)(sass@1.90.0)(terser@5.43.1)(tsx@4.20.4)(yaml@2.8.0))
|
||||
'@vitest/mocker': 3.2.4(msw@2.10.4(@types/node@24.0.10)(typescript@5.9.2))(vite@7.0.5(@types/node@24.0.10)(jiti@2.4.2)(lightningcss@1.30.1)(sass@1.90.0)(terser@5.43.1)(tsx@4.20.4)(yaml@2.8.0))
|
||||
'@vitest/pretty-format': 3.2.4
|
||||
'@vitest/runner': 3.2.4
|
||||
'@vitest/snapshot': 3.2.4
|
||||
|
|
|
|||
Loading…
Reference in New Issue