can1357
0d9ec354e7
- Added Gemini thinking-loop detection helpers for near-duplicate and verbatim output checks. - Wrapped `stream`, `streamPiNative`, and `streamSimple` dispatches with the loop guard. - Emitted retryable empty-content loop errors and stopped completion events on loop hits. - Added `enableGeminiThinkingLoopGuard` options for OpenAI compatibility with Gemini defaults and overrides.
1096 lines
40 KiB
TypeScript
1096 lines
40 KiB
TypeScript
import type { Effort } from "@oh-my-pi/pi-catalog/effort";
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import { isVertexExpressOpenAIUrl, isVertexRawPredictUrl } from "@oh-my-pi/pi-catalog/hosts";
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import {
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mapEffortToAnthropicAdaptiveEffort,
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mapEffortToGoogleThinkingLevel,
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minimumSupportedEffort,
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requireSupportedEffort,
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resolveWireModelId,
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} from "@oh-my-pi/pi-catalog/model-thinking";
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import { CATALOG_PROVIDERS, type ProviderCatalogEntry } from "@oh-my-pi/pi-catalog/provider-models";
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import { $env, $pickenv, extractHttpStatusFromError } from "@oh-my-pi/pi-utils";
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import { getCustomApi } from "./api-registry";
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import { AUTH_RETRY_STEPS, isApiKeyResolver, resolveRetryKey } from "./auth-retry";
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import { ProviderHttpError } from "./errors";
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import type { BedrockOptions } from "./providers/amazon-bedrock";
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import type { AnthropicOptions } from "./providers/anthropic";
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import type { CursorOptions } from "./providers/cursor";
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import { isGitLabDuoModel, streamGitLabDuo } from "./providers/gitlab-duo";
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import type { GoogleOptions } from "./providers/google";
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import { getVertexAccessToken } from "./providers/google-auth";
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import type { GoogleGeminiCliOptions } from "./providers/google-gemini-cli";
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import type { GoogleVertexOptions } from "./providers/google-vertex";
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import { isKimiModel, streamKimi } from "./providers/kimi";
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import type { OllamaChatOptions } from "./providers/ollama";
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import type { OpenAICompletionsOptions } from "./providers/openai-completions";
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import { streamPiNative } from "./providers/pi-native-client";
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// Heavy provider stream functions are imported lazily via register-builtins,
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// which wraps each provider module in a dynamic import. This keeps the
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// AWS SDK, google-auth-library, @google/genai, @bufbuild/protobuf, and
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// other provider SDKs out of the CLI startup parse graph. The
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// gitlab-duo / kimi / synthetic providers stay eager because their modules
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// export routing predicates (isGitLabDuoModel, isKimiModel, isSyntheticModel)
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// that must be callable synchronously before streaming begins, and their
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// modules are thin wrappers with no heavy SDK dependencies.
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import {
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streamAnthropic,
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streamAzureOpenAIResponses,
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streamBedrock,
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streamCursor,
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streamGoogle,
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streamGoogleGeminiCli,
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streamGoogleVertex,
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streamOllama,
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streamOpenAICodexResponses,
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streamOpenAICompletions,
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streamOpenAIResponses,
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} from "./providers/register-builtins";
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import { isSyntheticModel, streamSynthetic } from "./providers/synthetic";
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import { streamXAIResponses } from "./providers/xai-responses";
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import { isUsageLimitError } from "./rate-limit-utils";
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import { PROVIDER_REGISTRY } from "./registry";
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import type {
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Api,
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AssistantMessage,
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AssistantMessageEvent,
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Context,
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FetchImpl,
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Model,
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OptionsForApi,
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SimpleStreamOptions,
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StreamOptions,
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ThinkingBudgets,
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ToolChoice,
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} from "./types";
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import { AssistantMessageEventStream } from "./utils/event-stream";
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import { withRequestDebugFetch } from "./utils/request-debug";
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import { withGeminiThinkingLoopGuard } from "./utils/thinking-loop";
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function isGoogleVertexAuthenticatedModel(model: Model<Api>): boolean {
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return (
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model.provider === "google-vertex" &&
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((model.api === "openai-completions" && isVertexExpressOpenAIUrl(model.baseUrl)) ||
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(model.api === "anthropic-messages" && isVertexRawPredictUrl(model.baseUrl)))
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);
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}
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function createVertexAuthenticatedFetch(options: StreamOptions | undefined): FetchImpl {
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const baseFetch = options?.fetch ?? fetch;
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const vertexFetch = async (input: string | URL | Request, init?: RequestInit): Promise<Response> => {
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const token = await getVertexAccessToken({ signal: options?.signal, fetch: baseFetch });
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const headers = new Headers(init?.headers);
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headers.set("Authorization", `Bearer ${token}`);
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const rewritten = resolveVertexRequest(input);
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const url = rewritten instanceof Request ? rewritten.url : rewritten.toString();
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if (isVertexRawPredictUrl(url)) {
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const bodyText = await readVertexRequestBody(rewritten, init);
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const transformed = transformVertexAnthropicBody(bodyText);
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return baseFetch(url, {
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...init,
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method: init?.method ?? (rewritten instanceof Request ? rewritten.method : "POST"),
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headers,
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body: transformed,
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});
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}
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return baseFetch(rewritten, { ...init, headers });
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};
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return Object.assign(vertexFetch, baseFetch.preconnect ? { preconnect: baseFetch.preconnect } : {});
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}
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async function readVertexRequestBody(input: string | URL | Request, init: RequestInit | undefined): Promise<string> {
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if (input instanceof Request) return input.clone().text();
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const body = init?.body;
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if (typeof body === "string") return body;
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if (body instanceof Uint8Array) return new TextDecoder().decode(body);
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if (body instanceof ArrayBuffer) return new TextDecoder().decode(body);
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return "";
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}
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// Vertex Claude rejects the standard Anthropic body shape: the `model` field
|
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// is encoded in the URL path and `anthropic_version: "vertex-2023-10-16"` is
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// required in the JSON body instead of the `anthropic-version` HTTP header.
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function transformVertexAnthropicBody(bodyText: string): string {
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if (!bodyText) return bodyText;
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try {
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const payload = JSON.parse(bodyText) as Record<string, unknown>;
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delete payload.model;
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payload.anthropic_version = "vertex-2023-10-16";
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return JSON.stringify(payload);
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} catch {
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return bodyText;
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}
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}
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function resolveVertexRequest(input: string | URL | Request): string | URL | Request {
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const project = $env.GOOGLE_CLOUD_PROJECT || $env.GCP_PROJECT || $env.GCLOUD_PROJECT;
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const location = $env.GOOGLE_VERTEX_LOCATION || $env.GOOGLE_CLOUD_LOCATION || $env.VERTEX_LOCATION;
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if (!project || !location) return input;
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const rewriteUrl = (url: string): string => {
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const hasPlaceholder =
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url.includes("{project}") ||
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url.includes("{location}") ||
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url.includes("%7Bproject%7D") ||
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url.includes("%7Blocation%7D");
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const host = location === "global" ? "aiplatform.googleapis.com" : `${location}-aiplatform.googleapis.com`;
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const rewritten = hasPlaceholder
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? url
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.replace("https://{location}-aiplatform.googleapis.com", `https://${host}`)
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.replace("https://%7Blocation%7D-aiplatform.googleapis.com", `https://${host}`)
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.replaceAll("{project}", encodeURIComponent(project))
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.replaceAll("%7Bproject%7D", encodeURIComponent(project))
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.replaceAll("{location}", encodeURIComponent(location))
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.replaceAll("%7Blocation%7D", encodeURIComponent(location))
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: url;
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return rewritten.replace(":streamRawPredict/v1/messages", ":streamRawPredict");
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};
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if (input instanceof Request) {
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const rewrittenUrl = rewriteUrl(input.url);
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return rewrittenUrl === input.url ? input : new Request(rewrittenUrl, input);
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}
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if (input instanceof URL) {
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const rewrittenUrl = rewriteUrl(input.toString());
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return rewrittenUrl === input.toString() ? input : new URL(rewrittenUrl);
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}
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return rewriteUrl(input);
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}
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type KeyResolver = string | (() => string | undefined);
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const LEGACY_ENV_KEYS: Record<string, KeyResolver> = {
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// Non-provider / search-tool keys and API-name keys not modeled as registry provider defs.
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"azure-openai-responses": "AZURE_OPENAI_API_KEY",
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"llama.cpp": "LLAMA_CPP_API_KEY",
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exa: "EXA_API_KEY",
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jina: "JINA_API_KEY",
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brave: "BRAVE_API_KEY",
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};
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/**
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* Env fallbacks derived from the catalog table — the single source for plain
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* provider env-var names. Registry defs override with computed resolvers
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* (Foundry/ADC/Bedrock probes); legacy non-provider keys merge last.
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*/
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const CATALOG_ENTRY_ENV_KEYS = (CATALOG_PROVIDERS as readonly ProviderCatalogEntry[]).flatMap(provider => {
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const envVars = provider.envVars;
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if (!envVars || envVars.length === 0) return [];
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const resolver: KeyResolver = envVars.length === 1 ? envVars[0] : () => $pickenv(...envVars);
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return [[provider.id, resolver] as [string, KeyResolver]];
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});
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const serviceProviderMap: Record<string, KeyResolver> = {
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...Object.fromEntries(CATALOG_ENTRY_ENV_KEYS),
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...Object.fromEntries(
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PROVIDER_REGISTRY.flatMap(provider =>
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provider.envKeys != null ? [[provider.id, provider.envKeys] as [string, KeyResolver]] : [],
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),
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),
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...LEGACY_ENV_KEYS,
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};
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/**
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* Get API key for provider from known environment variables, e.g. OPENAI_API_KEY.
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*
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* Will not return API keys for providers that require OAuth tokens.
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* Checks Bun.env, then cwd/.env, then ~/.env.
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*/
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export function getEnvApiKey(provider: string): string | undefined {
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const resolver = serviceProviderMap[provider];
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if (typeof resolver === "string") {
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return $env[resolver];
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}
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|
return resolver?.();
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}
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|
|
/**
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|
* Name of the environment variable that backs `getEnvApiKey` for a provider,
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* when that provider maps to a single named variable (e.g. `github-copilot` →
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* `COPILOT_GITHUB_TOKEN`). Returns undefined for providers whose env fallback
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* is computed (multi-var pickers, Vertex ADC / Bedrock probes, …) since no
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* single variable name describes the source.
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*/
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export function getEnvApiKeyName(provider: string): string | undefined {
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const resolver = serviceProviderMap[provider];
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return typeof resolver === "string" ? resolver : undefined;
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}
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|
/**
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|
* Enumerate every provider that has an env-var fallback for `getEnvApiKey`.
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|
* Used by `omp auth-broker migrate --include-env` to discover env-sourced keys
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* that should be uploaded to the broker.
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*/
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export function listProvidersWithEnvKey(): string[] {
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return Object.keys(serviceProviderMap);
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}
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|
export function stream<TApi extends Api>(
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model: Model<TApi>,
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context: Context,
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options?: OptionsForApi<TApi>,
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): AssistantMessageEventStream {
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|
return withGeminiThinkingLoopGuard(model, options, opts => streamDispatch(model, context, opts));
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}
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|
function streamDispatch<TApi extends Api>(
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model: Model<TApi>,
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context: Context,
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|
options?: OptionsForApi<TApi>,
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|
): AssistantMessageEventStream {
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const requestOptions = withRequestDebugFetch(options as StreamOptions | undefined) as
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| OptionsForApi<TApi>
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| undefined;
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|
// Check custom API registry first (extension-provided APIs like "vertex-claude-api")
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|
const customApiProvider = getCustomApi(model.api);
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|
if (customApiProvider) {
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return customApiProvider.stream(model, context, requestOptions as StreamOptions);
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}
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|
if (isGitLabDuoModel(model)) {
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|
const apiKey = (requestOptions as StreamOptions | undefined)?.apiKey || getEnvApiKey(model.provider);
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if (!apiKey) {
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throw new Error(`No API key for provider: ${model.provider}`);
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|
}
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return streamGitLabDuo(model, context, {
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...(requestOptions as SimpleStreamOptions | undefined),
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apiKey,
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});
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}
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|
|
// Vertex AI uses Application Default Credentials, not API keys
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|
if (model.api === "google-vertex") {
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|
return streamGoogleVertex(model as Model<"google-vertex">, context, requestOptions as GoogleVertexOptions);
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|
} else if (model.api === "bedrock-converse-stream") {
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|
// Bedrock doesn't have any API keys instead it sources credentials from standard AWS env variables or from given AWS profile.
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|
return streamBedrock(
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model as Model<"bedrock-converse-stream">,
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context,
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(requestOptions || {}) as BedrockOptions,
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);
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}
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|
|
const apiKey = requestOptions?.apiKey || getEnvApiKey(model.provider);
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|
if (!apiKey) {
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throw new Error(`No API key for provider: ${model.provider}`);
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|
}
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|
const providerOptions = isGoogleVertexAuthenticatedModel(model)
|
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? {
|
|
...requestOptions,
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|
apiKey: "vertex-adc",
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|
fetch: createVertexAuthenticatedFetch(requestOptions as StreamOptions | undefined),
|
|
}
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|
: { ...requestOptions, apiKey };
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|
|
const api: Api = model.api;
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switch (api) {
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case "anthropic-messages": {
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const anthropicOptions = providerOptions as AnthropicOptions;
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return streamAnthropic(model as Model<"anthropic-messages">, context, {
|
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...anthropicOptions,
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isOAuth: anthropicOptions.isOAuth ?? model.isOAuth,
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});
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}
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|
|
case "openai-completions":
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return streamOpenAICompletions(model as Model<"openai-completions">, context, providerOptions as any);
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|
|
case "openai-responses": {
|
|
if (model.provider === "xai-oauth") {
|
|
return streamXAIResponses(model as Model<"openai-responses">, context, providerOptions as any);
|
|
}
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|
return streamOpenAIResponses(model as Model<"openai-responses">, context, providerOptions as any);
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|
}
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|
|
case "azure-openai-responses":
|
|
return streamAzureOpenAIResponses(model as Model<"azure-openai-responses">, context, providerOptions as any);
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|
|
|
case "openai-codex-responses":
|
|
return streamOpenAICodexResponses(model as Model<"openai-codex-responses">, context, providerOptions as any);
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|
|
|
case "google-generative-ai":
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|
return streamGoogle(model as Model<"google-generative-ai">, context, providerOptions);
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|
|
case "google-gemini-cli":
|
|
return streamGoogleGeminiCli(
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|
model as Model<"google-gemini-cli">,
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|
context,
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|
providerOptions as GoogleGeminiCliOptions,
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|
);
|
|
|
|
case "ollama-chat":
|
|
return streamOllama(model as Model<"ollama-chat">, context, providerOptions as OllamaChatOptions);
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|
|
|
case "cursor-agent":
|
|
return streamCursor(model as Model<"cursor-agent">, context, providerOptions as CursorOptions);
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|
|
|
default:
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|
throw new Error(`Unhandled API: ${api}`);
|
|
}
|
|
}
|
|
|
|
export async function complete<TApi extends Api>(
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model: Model<TApi>,
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context: Context,
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|
options?: OptionsForApi<TApi>,
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|
): Promise<AssistantMessage> {
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|
const s = stream(model, context, options);
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|
return s.result();
|
|
}
|
|
|
|
type AuthRetryFailure = {
|
|
error: unknown;
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|
bufferedEvents: AssistantMessageEvent[];
|
|
terminalEvent?: Extract<AssistantMessageEvent, { type: "error" }>;
|
|
};
|
|
|
|
function extractStatusFromAssistantError(message: AssistantMessage): number | undefined {
|
|
if (message.errorStatus !== undefined) return message.errorStatus;
|
|
if (!message.errorMessage) return undefined;
|
|
return extractHttpStatusFromError({ message: message.errorMessage });
|
|
}
|
|
|
|
function isRetryableUpstreamError(error: unknown, status: number | undefined, message: string | undefined): boolean {
|
|
// 401 means the credential is bad. Usage-limit phrasing (Codex's
|
|
// "You have hit your ChatGPT usage limit", Anthropic's "usage_limit_reached",
|
|
// Google's "resource_exhausted") means this account is parked but a
|
|
// sibling credential can usually pick the request up. Both are
|
|
// rotatable via `onAuthError` — the auth-gateway maps the former to
|
|
// `invalidateCredentialMatching` and the latter to `markUsageLimitReached`.
|
|
if (status === 401) return true;
|
|
void error;
|
|
return !!message && isUsageLimitError(message);
|
|
}
|
|
|
|
function createAssistantAuthError(message: AssistantMessage): Error {
|
|
const text = message.errorMessage ?? "Provider authentication failed";
|
|
const status = extractStatusFromAssistantError(message);
|
|
return status === undefined ? new Error(text) : new ProviderHttpError(text, status);
|
|
}
|
|
|
|
function emitBufferedEvents(stream: AssistantMessageEventStream, events: AssistantMessageEvent[]): void {
|
|
for (const event of events) {
|
|
stream.push(event);
|
|
}
|
|
}
|
|
|
|
export function streamSimple<TApi extends Api>(
|
|
model: Model<TApi>,
|
|
context: Context,
|
|
options?: SimpleStreamOptions,
|
|
): AssistantMessageEventStream {
|
|
const requestOptions = withRequestDebugFetch(options);
|
|
const apiKeyResolver = isApiKeyResolver(requestOptions?.apiKey) ? requestOptions.apiKey : undefined;
|
|
if (apiKeyResolver) {
|
|
const outer = new AssistantMessageEventStream();
|
|
const signal = requestOptions?.signal;
|
|
// One inner attempt against a resolved string key. When
|
|
// `captureAuthFailure` is set, a retryable auth error that arrives before
|
|
// any replay-unsafe event is buffered and returned (so the caller can
|
|
// retry with a fresh key) instead of surfaced. The terminal attempt
|
|
// clears the flag and emits whatever it gets.
|
|
const runAttempt = async (apiKey: string, captureAuthFailure: boolean): Promise<AuthRetryFailure | undefined> => {
|
|
const bufferedEvents: AssistantMessageEvent[] = [];
|
|
let emittedReplayUnsafeEvent = false;
|
|
const flushBuffered = (): void => {
|
|
emitBufferedEvents(outer, bufferedEvents);
|
|
bufferedEvents.length = 0;
|
|
};
|
|
|
|
try {
|
|
const inner = streamSimple(model, context, { ...requestOptions, apiKey });
|
|
for await (const event of inner) {
|
|
if (!emittedReplayUnsafeEvent && event.type === "start") {
|
|
bufferedEvents.push(event);
|
|
continue;
|
|
}
|
|
if (
|
|
!emittedReplayUnsafeEvent &&
|
|
captureAuthFailure &&
|
|
event.type === "error" &&
|
|
isRetryableUpstreamError(
|
|
event.error,
|
|
extractStatusFromAssistantError(event.error),
|
|
event.error.errorMessage,
|
|
)
|
|
) {
|
|
return { error: createAssistantAuthError(event.error), bufferedEvents, terminalEvent: event };
|
|
}
|
|
flushBuffered();
|
|
emittedReplayUnsafeEvent = true;
|
|
outer.push(event);
|
|
if (outer.done) return undefined;
|
|
}
|
|
flushBuffered();
|
|
if (!outer.done) outer.end(await inner.result());
|
|
} catch (error) {
|
|
if (
|
|
!emittedReplayUnsafeEvent &&
|
|
captureAuthFailure &&
|
|
isRetryableUpstreamError(
|
|
error,
|
|
extractHttpStatusFromError(error),
|
|
error instanceof Error ? error.message : undefined,
|
|
)
|
|
) {
|
|
return { error, bufferedEvents };
|
|
}
|
|
flushBuffered();
|
|
outer.fail(error);
|
|
}
|
|
return undefined;
|
|
};
|
|
const emitFailure = (failure: AuthRetryFailure): void => {
|
|
emitBufferedEvents(outer, failure.bufferedEvents);
|
|
if (failure.terminalEvent) {
|
|
outer.push(failure.terminalEvent);
|
|
} else {
|
|
outer.fail(failure.error);
|
|
}
|
|
};
|
|
|
|
void (async () => {
|
|
let lastKey: string | undefined;
|
|
try {
|
|
lastKey = (await apiKeyResolver({ lastChance: false, error: undefined, signal })) || undefined;
|
|
} catch (error) {
|
|
// A thrown resolver is a broker/OAuth/network failure, not a missing
|
|
// key — surface the cause instead of masking it as "No API key".
|
|
outer.fail(
|
|
new Error(
|
|
`Failed to resolve API key for provider ${model.provider}: ${error instanceof Error ? error.message : String(error)}`,
|
|
{ cause: error },
|
|
),
|
|
);
|
|
return;
|
|
}
|
|
if (lastKey === undefined) {
|
|
outer.fail(new Error(`No API key for provider: ${model.provider}`));
|
|
return;
|
|
}
|
|
let failure = await runAttempt(lastKey, true);
|
|
if (!failure) return;
|
|
// a/b/c policy: refresh the same account (lastChance=false), then
|
|
// switch to a sibling (lastChance=true). A step is skipped when the
|
|
// resolver yields the same key it just tried or `undefined`; the
|
|
// final step's attempt clears the capture flag so it emits directly.
|
|
for (let step = 0; step < AUTH_RETRY_STEPS.length; step++) {
|
|
// Caller aborted between attempts: don't mint a fresh token or fire
|
|
// another doomed request — emit the captured failure instead.
|
|
if (signal?.aborted) break;
|
|
const nextKey = await resolveRetryKey(apiKeyResolver, AUTH_RETRY_STEPS[step]!, failure.error, signal);
|
|
if (nextKey === undefined || nextKey === lastKey) continue;
|
|
lastKey = nextKey;
|
|
const isLastStep = step === AUTH_RETRY_STEPS.length - 1;
|
|
const next = await runAttempt(nextKey, !isLastStep);
|
|
if (!next) return;
|
|
failure = next;
|
|
}
|
|
emitFailure(failure);
|
|
})();
|
|
return outer;
|
|
}
|
|
|
|
// Pi-native transport short-circuits the per-provider dispatch entirely:
|
|
// the gateway resolves provider + credential server-side, so we don't
|
|
// need an `apiKey` from `getEnvApiKey` here — `options.apiKey` carries
|
|
// the gateway bearer instead. Comes BEFORE the custom-API check so
|
|
// extension-registered APIs can't accidentally override a configured
|
|
// pi-native transport.
|
|
if (model.transport === "pi-native") {
|
|
return withGeminiThinkingLoopGuard(model, requestOptions, opts => streamPiNative(model, context, opts));
|
|
}
|
|
|
|
// Check custom API registry (extension-provided APIs)
|
|
const customApiProvider = getCustomApi(model.api);
|
|
if (customApiProvider) {
|
|
return withGeminiThinkingLoopGuard(model, requestOptions, opts =>
|
|
customApiProvider.streamSimple(model, context, opts),
|
|
);
|
|
}
|
|
|
|
// Vertex AI uses Application Default Credentials, not API keys
|
|
if (model.api === "google-vertex") {
|
|
const providerOptions = mapOptionsForApi(model, requestOptions, undefined);
|
|
return stream(model, context, providerOptions);
|
|
} else if (model.api === "bedrock-converse-stream") {
|
|
// Bedrock doesn't have any API keys instead it sources credentials from standard AWS env variables or from given AWS profile.
|
|
const providerOptions = mapOptionsForApi(model, requestOptions, undefined);
|
|
return stream(model, context, providerOptions);
|
|
}
|
|
|
|
// The resolver form is handled by the wrapper above; only a static string
|
|
// key reaches this point.
|
|
const apiKey =
|
|
(typeof requestOptions?.apiKey === "string" ? requestOptions.apiKey : undefined) || getEnvApiKey(model.provider);
|
|
if (!apiKey) {
|
|
throw new Error(`No API key for provider: ${model.provider}`);
|
|
}
|
|
|
|
// GitLab Duo - wraps Anthropic/OpenAI behind GitLab AI Gateway direct access tokens
|
|
if (isGitLabDuoModel(model)) {
|
|
return streamGitLabDuo(model, context, {
|
|
...requestOptions,
|
|
apiKey,
|
|
});
|
|
}
|
|
|
|
// Kimi Code - route to dedicated handler that wraps OpenAI or Anthropic API
|
|
if (isKimiModel(model)) {
|
|
// Pass raw SimpleStreamOptions - streamKimi handles mapping internally
|
|
return streamKimi(model as Model<"openai-completions">, context, {
|
|
...requestOptions,
|
|
apiKey,
|
|
format: requestOptions?.kimiApiFormat ?? "anthropic",
|
|
});
|
|
}
|
|
|
|
// Synthetic - route to dedicated handler that wraps OpenAI or Anthropic API
|
|
if (isSyntheticModel(model)) {
|
|
// Pass raw SimpleStreamOptions - streamSynthetic handles mapping internally
|
|
return streamSynthetic(model as Model<"openai-completions">, context, {
|
|
...requestOptions,
|
|
apiKey,
|
|
format: requestOptions?.syntheticApiFormat ?? "openai", // Default to OpenAI format
|
|
});
|
|
}
|
|
const providerOptions = mapOptionsForApi(model, requestOptions, apiKey);
|
|
return stream(model, context, providerOptions);
|
|
}
|
|
|
|
export async function completeSimple<TApi extends Api>(
|
|
model: Model<TApi>,
|
|
context: Context,
|
|
options?: SimpleStreamOptions,
|
|
): Promise<AssistantMessage> {
|
|
const s = streamSimple(model, context, options);
|
|
return s.result();
|
|
}
|
|
|
|
const MIN_OUTPUT_TOKENS = 1024;
|
|
// Fallback total output cap for models whose catalog entry has no maxTokens.
|
|
const OUTPUT_CAP_WHEN_UNKNOWN = 64_000;
|
|
function maxTokensWithThinkingBudget(
|
|
baseMaxTokens: number | undefined,
|
|
modelMaxTokens: number | null,
|
|
thinkingBudget: number,
|
|
): number {
|
|
const uncappedMaxTokens = baseMaxTokens === undefined ? OUTPUT_CAP_WHEN_UNKNOWN : baseMaxTokens + thinkingBudget;
|
|
return Math.min(uncappedMaxTokens, modelMaxTokens ?? Number.POSITIVE_INFINITY);
|
|
}
|
|
export const OUTPUT_FALLBACK_BUFFER = 4000;
|
|
const ANTHROPIC_USE_INTERLEAVED_THINKING = Bun.env.PI_NO_INTERLEAVED_THINKING !== "1";
|
|
|
|
export const ANTHROPIC_THINKING: Record<Effort, number> = {
|
|
minimal: 1024,
|
|
low: 4096,
|
|
medium: 8192,
|
|
high: 16384,
|
|
xhigh: 32768,
|
|
};
|
|
|
|
const GOOGLE_THINKING: Record<Effort, number> = {
|
|
minimal: 1024,
|
|
low: 4096,
|
|
medium: 8192,
|
|
high: 16384,
|
|
xhigh: 24575,
|
|
};
|
|
|
|
const BEDROCK_CLAUDE_THINKING: Record<Effort, number> = {
|
|
minimal: 1024,
|
|
low: 2048,
|
|
medium: 8192,
|
|
high: 16384,
|
|
xhigh: 16384,
|
|
};
|
|
|
|
function resolveBedrockThinkingBudget(
|
|
model: Model<"bedrock-converse-stream">,
|
|
options?: SimpleStreamOptions,
|
|
): { budget: number; level: Effort } | null {
|
|
if (!options?.reasoning || !model.reasoning) return null;
|
|
const level = requireSupportedEffort(model, options.reasoning);
|
|
const budget = options.thinkingBudgets?.[level] ?? BEDROCK_CLAUDE_THINKING[level];
|
|
return { budget, level };
|
|
}
|
|
|
|
export function mapAnthropicToolChoice(choice?: ToolChoice): AnthropicOptions["toolChoice"] {
|
|
if (!choice) return undefined;
|
|
if (typeof choice === "string") {
|
|
if (choice === "required") return "any";
|
|
if (choice === "auto" || choice === "none" || choice === "any") return choice;
|
|
return undefined;
|
|
}
|
|
if (choice.type === "tool") {
|
|
return choice.name ? { type: "tool", name: choice.name } : undefined;
|
|
}
|
|
if (choice.type === "function") {
|
|
const name = "function" in choice ? choice.function?.name : choice.name;
|
|
return name ? { type: "tool", name } : undefined;
|
|
}
|
|
return undefined;
|
|
}
|
|
|
|
export function mapGoogleToolChoice(
|
|
choice?: ToolChoice,
|
|
): GoogleOptions["toolChoice"] | GoogleGeminiCliOptions["toolChoice"] | GoogleVertexOptions["toolChoice"] {
|
|
if (!choice) return undefined;
|
|
if (typeof choice === "string") {
|
|
if (choice === "required") return "any";
|
|
if (choice === "auto" || choice === "none" || choice === "any") return choice;
|
|
return undefined;
|
|
}
|
|
// Named-tool routing on Google: emit an `ANY`-mode allow-list of one entry,
|
|
// mirroring the Anthropic mapper that returns `{type: "tool", name}`.
|
|
if (choice.type === "tool") {
|
|
return choice.name ? { mode: "ANY", allowedFunctionNames: [choice.name] } : undefined;
|
|
}
|
|
if (choice.type === "function") {
|
|
const name = "function" in choice ? choice.function?.name : choice.name;
|
|
return name ? { mode: "ANY", allowedFunctionNames: [name] } : undefined;
|
|
}
|
|
return undefined;
|
|
}
|
|
|
|
function mapOpenAiToolChoice(choice?: ToolChoice): OpenAICompletionsOptions["toolChoice"] {
|
|
if (!choice) return undefined;
|
|
if (typeof choice === "string") {
|
|
if (choice === "any") return "required";
|
|
if (choice === "auto" || choice === "none" || choice === "required") return choice;
|
|
return undefined;
|
|
}
|
|
if (choice.type === "tool") {
|
|
return choice.name ? { type: "function", function: { name: choice.name } } : undefined;
|
|
}
|
|
if (choice.type === "function") {
|
|
const name = "function" in choice ? choice.function?.name : choice.name;
|
|
return name ? { type: "function", function: { name } } : undefined;
|
|
}
|
|
return undefined;
|
|
}
|
|
|
|
function resolveOpenAiReasoningEffort<TApi extends Api>(
|
|
model: Model<TApi>,
|
|
options?: SimpleStreamOptions,
|
|
): Effort | undefined {
|
|
const reasoning = options?.reasoning;
|
|
if (!reasoning || !model.reasoning) return undefined;
|
|
// Models that reason natively but expose no effort dial carry
|
|
// `thinking: undefined` (baked at build time from
|
|
// `compat.supportsReasoningEffort: false` on openai-responses*). The
|
|
// wire-side omitReasoningEffort gate (providers/xai-responses.ts:78) is the
|
|
// actual strip; returning undefined here avoids a redundant
|
|
// requireSupportedEffort throw that would defeat the gate and surface a
|
|
// confusing "Compaction failed: Thinking effort high is not supported
|
|
// by..." to the user.
|
|
if (!model.thinking) return undefined;
|
|
return requireSupportedEffort(model, reasoning);
|
|
}
|
|
|
|
const castApi = <TApi extends Api>(api: OptionsForApi<TApi>): OptionsForApi<Api> => api as OptionsForApi<Api>;
|
|
|
|
/**
|
|
* Mandatory-reasoning endpoints (`thinking.requiresEffort`) reject disabled
|
|
* or omitted thinking ("Reasoning is mandatory for this endpoint and cannot
|
|
* be disabled") — clamp to the lowest supported effort instead.
|
|
* `suppressWhenOff` models handle off provider-side via explicit wire
|
|
* suppression. Collapsed pairs interplay: pair derivation strips member
|
|
* flags (off routes to a bare SKU that CAN disable), while identity backfill
|
|
* re-flags pairs whose logical id is itself mandatory (Gemini 3.x) — there
|
|
* the clamp wins and the floored effort routes to the thinking SKU.
|
|
*/
|
|
function normalizeMandatoryReasoningOptions<TApi extends Api>(
|
|
model: Model<TApi>,
|
|
options?: SimpleStreamOptions,
|
|
): SimpleStreamOptions | undefined {
|
|
if (
|
|
!model.reasoning ||
|
|
!model.thinking?.requiresEffort ||
|
|
model.thinking.suppressWhenOff ||
|
|
(options?.reasoning !== undefined && !options.disableReasoning)
|
|
) {
|
|
return options;
|
|
}
|
|
const floor = minimumSupportedEffort(model);
|
|
if (floor === undefined) return options;
|
|
return { ...options, reasoning: floor, disableReasoning: undefined };
|
|
}
|
|
|
|
function mapOptionsForApi<TApi extends Api>(
|
|
model: Model<TApi>,
|
|
rawOptions?: SimpleStreamOptions,
|
|
apiKey?: string,
|
|
): OptionsForApi<TApi> {
|
|
const options = normalizeMandatoryReasoningOptions(model, rawOptions);
|
|
const base = {
|
|
temperature: options?.temperature,
|
|
topP: options?.topP,
|
|
topK: options?.topK,
|
|
minP: options?.minP,
|
|
presencePenalty: options?.presencePenalty,
|
|
repetitionPenalty: options?.repetitionPenalty,
|
|
maxTokens: options?.maxTokens ?? model.maxTokens ?? undefined,
|
|
signal: options?.signal,
|
|
apiKey: apiKey ?? (typeof options?.apiKey === "string" ? options.apiKey : undefined),
|
|
cacheRetention: options?.cacheRetention,
|
|
headers: options?.headers,
|
|
initiatorOverride: options?.initiatorOverride,
|
|
maxRetryDelayMs: options?.maxRetryDelayMs,
|
|
metadata: options?.metadata,
|
|
taskBudget: options?.taskBudget,
|
|
sessionId: options?.sessionId,
|
|
promptCacheKey: options?.promptCacheKey,
|
|
streamFirstEventTimeoutMs: options?.streamFirstEventTimeoutMs,
|
|
streamIdleTimeoutMs: options?.streamIdleTimeoutMs,
|
|
providerSessionState: options?.providerSessionState,
|
|
onPayload: options?.onPayload,
|
|
onResponse: options?.onResponse,
|
|
onSseEvent: options?.onSseEvent,
|
|
execHandlers: options?.execHandlers,
|
|
fetch: options?.fetch,
|
|
};
|
|
|
|
switch (model.api) {
|
|
case "anthropic-messages": {
|
|
// Explicitly disable thinking when reasoning is not specified or model doesn't support it
|
|
const reasoning = options?.reasoning;
|
|
if (!reasoning || !model.reasoning) {
|
|
return castApi<"anthropic-messages">({
|
|
...base,
|
|
requestModelId: resolveWireModelId(model, undefined),
|
|
thinkingEnabled: false,
|
|
toolChoice: mapAnthropicToolChoice(options?.toolChoice),
|
|
thinkingDisplay: options?.hideThinkingSummary ? "omitted" : undefined,
|
|
serviceTier: options?.serviceTier,
|
|
});
|
|
}
|
|
|
|
let thinkingBudget = options.thinkingBudgets?.[reasoning] ?? ANTHROPIC_THINKING[reasoning];
|
|
if (thinkingBudget <= 0) {
|
|
return castApi<"anthropic-messages">({
|
|
...base,
|
|
requestModelId: resolveWireModelId(model, undefined),
|
|
thinkingEnabled: false,
|
|
toolChoice: mapAnthropicToolChoice(options?.toolChoice),
|
|
thinkingDisplay: options?.hideThinkingSummary ? "omitted" : undefined,
|
|
serviceTier: options?.serviceTier,
|
|
});
|
|
}
|
|
|
|
// For Opus 4.6+ and Sonnet 4.6+: use adaptive thinking with effort level
|
|
// For older models: use budget-based thinking
|
|
if (model.thinking?.mode === "anthropic-adaptive") {
|
|
const effort = mapEffortToAnthropicAdaptiveEffort(model, reasoning);
|
|
return castApi<"anthropic-messages">({
|
|
...base,
|
|
requestModelId: resolveWireModelId(model, reasoning),
|
|
thinkingEnabled: true,
|
|
effort,
|
|
toolChoice: mapAnthropicToolChoice(options?.toolChoice),
|
|
thinkingDisplay: options?.hideThinkingSummary ? "omitted" : undefined,
|
|
serviceTier: options?.serviceTier,
|
|
});
|
|
}
|
|
|
|
if (ANTHROPIC_USE_INTERLEAVED_THINKING) {
|
|
return castApi<"anthropic-messages">({
|
|
...base,
|
|
requestModelId: resolveWireModelId(model, reasoning),
|
|
thinkingEnabled: true,
|
|
thinkingBudgetTokens: thinkingBudget,
|
|
toolChoice: mapAnthropicToolChoice(options?.toolChoice),
|
|
thinkingDisplay: options?.hideThinkingSummary ? "omitted" : undefined,
|
|
serviceTier: options?.serviceTier,
|
|
});
|
|
}
|
|
|
|
// Caller's maxTokens is desired output, so add thinking budget on top. With no caller/model cap, use a finite total fallback.
|
|
const maxTokens = maxTokensWithThinkingBudget(base.maxTokens, model.maxTokens, thinkingBudget);
|
|
|
|
// If not enough room for thinking + output, reduce thinking budget
|
|
if (maxTokens <= thinkingBudget) {
|
|
thinkingBudget = maxTokens - MIN_OUTPUT_TOKENS;
|
|
}
|
|
|
|
// If thinking budget is too low, disable thinking
|
|
if (thinkingBudget <= 0) {
|
|
return castApi<"anthropic-messages">({
|
|
...base,
|
|
requestModelId: resolveWireModelId(model, undefined),
|
|
thinkingEnabled: false,
|
|
toolChoice: mapAnthropicToolChoice(options?.toolChoice),
|
|
thinkingDisplay: options?.hideThinkingSummary ? "omitted" : undefined,
|
|
serviceTier: options?.serviceTier,
|
|
});
|
|
} else {
|
|
return castApi<"anthropic-messages">({
|
|
...base,
|
|
maxTokens,
|
|
requestModelId: resolveWireModelId(model, reasoning),
|
|
thinkingEnabled: true,
|
|
thinkingBudgetTokens: thinkingBudget,
|
|
toolChoice: mapAnthropicToolChoice(options?.toolChoice),
|
|
thinkingDisplay: options?.hideThinkingSummary ? "omitted" : undefined,
|
|
serviceTier: options?.serviceTier,
|
|
});
|
|
}
|
|
}
|
|
|
|
case "bedrock-converse-stream": {
|
|
const bedrockBase: BedrockOptions = {
|
|
...base,
|
|
reasoning: options?.reasoning,
|
|
thinkingBudgets: options?.thinkingBudgets,
|
|
toolChoice: mapAnthropicToolChoice(options?.toolChoice),
|
|
thinkingDisplay: options?.hideThinkingSummary ? "omitted" : undefined,
|
|
};
|
|
// Adaptive mode sends effort directly, no budget_tokens — skip budget inflation.
|
|
if (model.thinking?.mode === "anthropic-adaptive") {
|
|
return castApi<"bedrock-converse-stream">(bedrockBase);
|
|
}
|
|
const budgetInfo = resolveBedrockThinkingBudget(model as Model<"bedrock-converse-stream">, options);
|
|
if (!budgetInfo) return bedrockBase as OptionsForApi<TApi>;
|
|
let maxTokens = bedrockBase.maxTokens ?? model.maxTokens ?? OUTPUT_CAP_WHEN_UNKNOWN;
|
|
let thinkingBudgets = bedrockBase.thinkingBudgets;
|
|
if (maxTokens <= budgetInfo.budget) {
|
|
const desiredMaxTokens = Math.min(
|
|
model.maxTokens ?? Number.POSITIVE_INFINITY,
|
|
budgetInfo.budget + MIN_OUTPUT_TOKENS,
|
|
);
|
|
if (desiredMaxTokens > maxTokens) {
|
|
maxTokens = desiredMaxTokens;
|
|
}
|
|
}
|
|
if (maxTokens <= budgetInfo.budget) {
|
|
const adjustedBudget = Math.max(0, maxTokens - MIN_OUTPUT_TOKENS);
|
|
thinkingBudgets = { ...(thinkingBudgets ?? {}), [budgetInfo.level]: adjustedBudget };
|
|
}
|
|
return castApi<"bedrock-converse-stream">({ ...bedrockBase, maxTokens, thinkingBudgets });
|
|
}
|
|
|
|
case "openai-completions":
|
|
return castApi<"openai-completions">({
|
|
...base,
|
|
reasoning: resolveOpenAiReasoningEffort(model, options),
|
|
disableReasoning: options?.disableReasoning,
|
|
toolChoice: mapOpenAiToolChoice(options?.toolChoice),
|
|
serviceTier: options?.serviceTier,
|
|
openrouterVariant: options?.openrouterVariant,
|
|
maxTokensExplicit: rawOptions?.maxTokens !== undefined,
|
|
});
|
|
|
|
case "openai-responses":
|
|
return castApi<"openai-responses">({
|
|
...base,
|
|
reasoning: resolveOpenAiReasoningEffort(model, options),
|
|
toolChoice: mapOpenAiToolChoice(options?.toolChoice),
|
|
serviceTier: options?.serviceTier,
|
|
reasoningSummary: options?.hideThinkingSummary ? null : undefined,
|
|
});
|
|
|
|
case "azure-openai-responses":
|
|
return castApi<"azure-openai-responses">({
|
|
...base,
|
|
reasoning: resolveOpenAiReasoningEffort(model, options),
|
|
toolChoice: mapOpenAiToolChoice(options?.toolChoice),
|
|
serviceTier: options?.serviceTier,
|
|
reasoningSummary: options?.hideThinkingSummary ? null : undefined,
|
|
});
|
|
|
|
case "openai-codex-responses":
|
|
return castApi<"openai-codex-responses">({
|
|
...base,
|
|
reasoning: resolveOpenAiReasoningEffort(model, options),
|
|
toolChoice: mapOpenAiToolChoice(options?.toolChoice),
|
|
serviceTier: options?.serviceTier,
|
|
preferWebsockets: options?.preferWebsockets,
|
|
reasoningSummary: options?.hideThinkingSummary ? null : undefined,
|
|
});
|
|
|
|
case "google-generative-ai": {
|
|
// Explicitly disable thinking when reasoning is not specified or model doesn't support it
|
|
// This is needed because Gemini has "dynamic thinking" enabled by default
|
|
const reasoning = options?.reasoning;
|
|
if (!reasoning || !model.reasoning) {
|
|
return castApi<"google-generative-ai">({
|
|
...base,
|
|
thinking: { enabled: false },
|
|
toolChoice: mapGoogleToolChoice(options?.toolChoice),
|
|
});
|
|
}
|
|
|
|
const googleModel = model as Model<"google-generative-ai">;
|
|
const effort = requireSupportedEffort(googleModel, reasoning);
|
|
|
|
// Gemini 3+ models use thinkingLevel exclusively instead of thinkingBudget.
|
|
// https://ai.google.dev/gemini-api/docs/thinking#set-budget
|
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if (googleModel.thinking?.mode === "google-level") {
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return castApi<"google-generative-ai">({
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...base,
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thinking: {
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enabled: true,
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level: mapEffortToGoogleThinkingLevel(effort),
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},
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toolChoice: mapGoogleToolChoice(options?.toolChoice),
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});
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|
}
|
|
|
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return castApi<"google-gemini-cli">({
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|
...base,
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thinking: {
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|
enabled: true,
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budgetTokens: getGoogleBudget(googleModel, effort, options?.thinkingBudgets),
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},
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|
toolChoice: mapGoogleToolChoice(options?.toolChoice),
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});
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}
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|
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case "google-gemini-cli": {
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const reasoning = options?.reasoning;
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const toolChoice = mapGoogleToolChoice(options?.toolChoice);
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if (reasoning && model.reasoning) {
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const effort = requireSupportedEffort(model, reasoning);
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|
|
|
// Gemini 3+ models use thinkingLevel instead of thinkingBudget
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|
if (model.thinking?.mode === "google-level") {
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|
return castApi<"google-gemini-cli">({
|
|
...base,
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|
requestModelId: resolveWireModelId(model, effort),
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|
thinking: {
|
|
enabled: true,
|
|
level: mapEffortToGoogleThinkingLevel(effort),
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|
},
|
|
toolChoice,
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|
antigravityEndpointMode: options?.antigravityEndpointMode,
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|
});
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|
}
|
|
|
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let thinkingBudget =
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|
options.thinkingBudgets?.[effort] ?? model.thinking?.effortBudgets?.[effort] ?? GOOGLE_THINKING[effort];
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|
|
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// Caller's maxTokens is desired output, so add thinking budget on top. With no caller/model cap, use a finite total fallback.
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|
const maxTokens = maxTokensWithThinkingBudget(base.maxTokens, model.maxTokens, thinkingBudget);
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|
|
|
// If not enough room for thinking + output, reduce thinking budget
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|
if (maxTokens <= thinkingBudget) {
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|
thinkingBudget = Math.max(0, maxTokens - MIN_OUTPUT_TOKENS);
|
|
}
|
|
|
|
if (thinkingBudget > 0) {
|
|
return castApi<"google-gemini-cli">({
|
|
...base,
|
|
maxTokens,
|
|
requestModelId: resolveWireModelId(model, effort),
|
|
thinking: { enabled: true, budgetTokens: thinkingBudget },
|
|
toolChoice,
|
|
antigravityEndpointMode: options?.antigravityEndpointMode,
|
|
});
|
|
}
|
|
// Budget clamped to zero — fall through to the thinking-off path.
|
|
}
|
|
|
|
const thinking: GoogleGeminiCliOptions["thinking"] = { enabled: false };
|
|
if (model.reasoning && model.thinking?.suppressWhenOff) {
|
|
// CCA re-applies the per-id baked server default when the config
|
|
// is omitted; suppression must be explicit on the wire.
|
|
thinking.suppress = model.thinking.mode === "google-level" ? { level: "MINIMAL" } : { budget: 0 };
|
|
}
|
|
return castApi<"google-gemini-cli">({
|
|
...base,
|
|
requestModelId: resolveWireModelId(model, undefined),
|
|
thinking,
|
|
toolChoice,
|
|
antigravityEndpointMode: options?.antigravityEndpointMode,
|
|
});
|
|
}
|
|
|
|
case "google-vertex": {
|
|
// Explicitly disable thinking when reasoning is not specified or model doesn't support it
|
|
const reasoning = options?.reasoning;
|
|
if (!reasoning || !model.reasoning) {
|
|
return castApi<"google-vertex">({
|
|
...base,
|
|
thinking: { enabled: false },
|
|
toolChoice: mapGoogleToolChoice(options?.toolChoice),
|
|
});
|
|
}
|
|
|
|
const vertexModel = model as Model<"google-vertex">;
|
|
const effort = requireSupportedEffort(vertexModel, reasoning);
|
|
const geminiModel = vertexModel as unknown as Model<"google-generative-ai">;
|
|
|
|
if (geminiModel.thinking?.mode === "google-level") {
|
|
return castApi<"google-vertex">({
|
|
...base,
|
|
thinking: {
|
|
enabled: true,
|
|
level: mapEffortToGoogleThinkingLevel(effort),
|
|
},
|
|
toolChoice: mapGoogleToolChoice(options?.toolChoice),
|
|
});
|
|
}
|
|
|
|
return castApi<"google-vertex">({
|
|
...base,
|
|
thinking: {
|
|
enabled: true,
|
|
budgetTokens: getGoogleBudget(geminiModel, effort, options?.thinkingBudgets),
|
|
},
|
|
toolChoice: mapGoogleToolChoice(options?.toolChoice),
|
|
});
|
|
}
|
|
|
|
case "ollama-chat":
|
|
return castApi<"ollama-chat">({
|
|
...base,
|
|
reasoning: resolveOpenAiReasoningEffort(model, options),
|
|
disableReasoning: options?.disableReasoning,
|
|
toolChoice: options?.toolChoice,
|
|
});
|
|
|
|
case "cursor-agent": {
|
|
const execHandlers = options?.cursorExecHandlers ?? options?.execHandlers;
|
|
const onToolResult = options?.cursorOnToolResult ?? execHandlers?.onToolResult;
|
|
return castApi<"cursor-agent">({
|
|
...base,
|
|
execHandlers,
|
|
onToolResult,
|
|
});
|
|
}
|
|
|
|
default:
|
|
throw new Error(`Unhandled API in mapOptionsForApi: ${model.api}`);
|
|
}
|
|
}
|
|
|
|
function getGoogleBudget(
|
|
model: Model<"google-generative-ai">,
|
|
effort: Effort,
|
|
customBudgets?: ThinkingBudgets,
|
|
): number {
|
|
requireSupportedEffort(model, effort);
|
|
|
|
// Custom budgets take precedence if provided for this level
|
|
if (customBudgets?.[effort] !== undefined) {
|
|
return customBudgets[effort]!;
|
|
}
|
|
|
|
// See https://ai.google.dev/gemini-api/docs/thinking#set-budget
|
|
if (model.id.includes("2.5-")) {
|
|
switch (effort) {
|
|
case "minimal":
|
|
return 128;
|
|
case "low":
|
|
return 2048;
|
|
case "medium":
|
|
return 8192;
|
|
default:
|
|
return model.id.includes("2.5-flash") ? 24576 : 32768;
|
|
}
|
|
}
|
|
|
|
// Unknown model - use dynamic
|
|
return -1;
|
|
}
|